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  • Adapting Large Language Models via Reading Comprehension

    Adapting Large Language Models via Reading Comprehension

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

    OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • PDFTriage: Question Answering over Long, Structured Documents

    PDFTriage: Question Answering over Long, Structured Documents

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference Using Sorted Fine-Tuning (SoFT)

    Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference Using Sorted Fine-Tuning (SoFT)

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

    An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • MindAgent: Emergent Gaming Interaction

    MindAgent: Emergent Gaming Interaction

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?

    Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  •   Recovering from Privacy-Preserving Masking with Large Language Models

    Recovering from Privacy-Preserving Masking with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

    S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • Augmenting text for spoken language understanding with Large Language Models

    Augmenting text for spoken language understanding with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • Language Modeling Is Compression

    Language Modeling Is Compression

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • Baichuan 2: Open Large-scale Language Models

    Baichuan 2: Open Large-scale Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • Stabilizing RLHF through Advantage Model and Selective Rehearsal

    Stabilizing RLHF through Advantage Model and Selective Rehearsal

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • Chain-of-Verification Reduces Hallucination in Large Language Models

    Chain-of-Verification Reduces Hallucination in Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • LMDX: Language Model-based Document Information Extraction and Localization

    LMDX: Language Model-based Document Information Extraction and Localization

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  •   SlimPajama-DC: Understanding Data Combinations for LLM Training

    SlimPajama-DC: Understanding Data Combinations for LLM Training

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Contrastive Decoding Improves Reasoning in Large Language Models

    Contrastive Decoding Improves Reasoning in Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

    CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • A Data Source for Reasoning Embodied Agents

    A Data Source for Reasoning Embodied Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Leveraging Contextual Information for Effective Entity Salience Detection

    Leveraging Contextual Information for Effective Entity Salience Detection

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • LASER: LLM Agent with State-Space Exploration for Web Navigation

    LASER: LLM Agent with State-Space Exploration for Web Navigation

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Sparse Autoencoders Find Highly Interpretable Features in Language Models

    Sparse Autoencoders Find Highly Interpretable Features in Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Investigating Answerability of LLMs for Long-Form Question Answering

    Investigating Answerability of LLMs for Long-Form Question Answering

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Scaling Laws for Sparsely-Connected Foundation Models

    Scaling Laws for Sparsely-Connected Foundation Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

    Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Ambiguity-Aware In-Context Learning with Large Language Models

    Ambiguity-Aware In-Context Learning with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?

    Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

    Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Agents: An Open-source Framework for Autonomous Language Agents

    Agents: An Open-source Framework for Autonomous Language Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Statistical Rejection Sampling Improves Preference Optimization

    Statistical Rejection Sampling Improves Preference Optimization

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Large Language Models for Compiler Optimization

    Large Language Models for Compiler Optimization

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • AstroLLaMA: Towards Specialized Foundation Models in Astronomy

    AstroLLaMA: Towards Specialized Foundation Models in Astronomy

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Large Language Model for Science: A Study on P vs. NP

    Large Language Model for Science: A Study on P vs. NP

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Efficient Memory Management for Large Language Model Serving with PagedAttention

    Efficient Memory Management for Large Language Model Serving with PagedAttention

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning

    FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

    Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

    When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Neurons in Large Language Models: Dead, N-gram, Positional

    Neurons in Large Language Models: Dead, N-gram, Positional

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Textbooks Are All You Need II: phi-1.5 technical report

    Textbooks Are All You Need II: phi-1.5 technical report

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

    DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

    From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • XGen-7B Technical Report

    XGen-7B Technical Report

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

    DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • GPT Can Solve Mathematical Problems Without a Calculator

    GPT Can Solve Mathematical Problems Without a Calculator

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Large Language Models as Optimizers

    Large Language Models as Optimizers

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Efficient RLHF: Reducing the Memory Usage of PPO

    Efficient RLHF: Reducing the Memory Usage of PPO

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

    ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]

    Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Llama 2: Open Foundation and Fine-Tuned Chat Models [Commentary]

    Llama 2: Open Foundation and Fine-Tuned Chat Models [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Challenges and Applications of Large Language Models [Summary]

    Challenges and Applications of Large Language Models [Summary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]

    LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]

    ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

    FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Graph of Thoughts: Solving Elaborate Problems with Large Language Models

    Graph of Thoughts: Solving Elaborate Problems with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Efficient Guided Generation for Large Language Models

    Efficient Guided Generation for Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Predicting transcriptional outcomes of novel multigene perturbations with GEARS

    Predicting transcriptional outcomes of novel multigene perturbations with GEARS

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • A Survey on Model Compression for Large Language Models

    A Survey on Model Compression for Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

    From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • LLM As DBA

    LLM As DBA

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Self-Alignment with Instruction Backtranslation

    Self-Alignment with Instruction Backtranslation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

    RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior

    Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

    BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

    The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Can Programming Languages Boost Each Other via Instruction Tuning?

    Can Programming Languages Boost Each Other via Instruction Tuning?

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

    Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

    MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • SoTaNa: The Open-Source Software Development Assistant

    SoTaNa: The Open-Source Software Development Assistant

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Teach LLMs to Personalize -- An Approach inspired by Writing Education

    Teach LLMs to Personalize -- An Approach inspired by Writing Education

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

    RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

    Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

    The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • CausalLM is not optimal for in-context learning

    CausalLM is not optimal for in-context learning

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • OctoPack: Instruction Tuning Code Large Language Models

    OctoPack: Instruction Tuning Code Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Enhancing Network Management Using Code Generated by Large Language Models

    Enhancing Network Management Using Code Generated by Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Improving Joint Speech-Text Representations Without Alignment

    Improving Joint Speech-Text Representations Without Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

    BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • PIPPA: A Partially Synthetic Conversational Dataset

    PIPPA: A Partially Synthetic Conversational Dataset

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Self-Alignment with Instruction Backtranslation

    Self-Alignment with Instruction Backtranslation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • OpenProteinSet: Training data for structural biology at scale

    OpenProteinSet: Training data for structural biology at scale

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Accelerating LLM Inference with Staged Speculative Decoding

    Accelerating LLM Inference with Staged Speculative Decoding

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Shepherd: A Critic for Language Model Generation

    Shepherd: A Critic for Language Model Generation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore

    SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Simple synthetic data reduces sycophancy in large language models

    Simple synthetic data reduces sycophancy in large language models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ FinanceFinance
  • Adapting Large Language Models via Reading Comprehension

    Adapting Large Language Models via Reading Comprehension

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
/ HealthcareHealthcare
  • Adapting Large Language Models via Reading Comprehension

    Adapting Large Language Models via Reading Comprehension

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

    Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Predicting transcriptional outcomes of novel multigene perturbations with GEARS

    Predicting transcriptional outcomes of novel multigene perturbations with GEARS

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

    BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

    MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • OpenProteinSet: Training data for structural biology at scale

    OpenProteinSet: Training data for structural biology at scale

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ LegalLegal
  • Adapting Large Language Models via Reading Comprehension

    Adapting Large Language Models via Reading Comprehension

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore

    SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ PromptingPrompting
  • Adapting Large Language Models via Reading Comprehension

    Adapting Large Language Models via Reading Comprehension

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

    Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

    DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

    From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

    DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Large Language Models as Optimizers

    Large Language Models as Optimizers

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Graph of Thoughts: Solving Elaborate Problems with Large Language Models

    Graph of Thoughts: Solving Elaborate Problems with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

    Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

    The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ MultilingualMultilingual
  • OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

    OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Baichuan 2: Open Large-scale Language Models

    Baichuan 2: Open Large-scale Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

    CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?

    Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

    The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

    Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

    The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Improving Joint Speech-Text Representations Without Alignment

    Improving Joint Speech-Text Representations Without Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ RetrievalRetrieval
  • PDFTriage: Question Answering over Long, Structured Documents

    PDFTriage: Question Answering over Long, Structured Documents

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

    RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ Fine-tuningFine-tuning
  • Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference Using Sorted Fine-Tuning (SoFT)

    Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference Using Sorted Fine-Tuning (SoFT)

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Leveraging Contextual Information for Effective Entity Salience Detection

    Leveraging Contextual Information for Effective Entity Salience Detection

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning

    FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ Instruction TuningInstruction Tuning
  • An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

    An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • XGen-7B Technical Report

    XGen-7B Technical Report

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Self-Alignment with Instruction Backtranslation

    Self-Alignment with Instruction Backtranslation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Can Programming Languages Boost Each Other via Instruction Tuning?

    Can Programming Languages Boost Each Other via Instruction Tuning?

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

    MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • OctoPack: Instruction Tuning Code Large Language Models

    OctoPack: Instruction Tuning Code Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Self-Alignment with Instruction Backtranslation

    Self-Alignment with Instruction Backtranslation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ MultimodalMultimodal
  • An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

    An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Natural Language Supervision for General-Purpose Audio Representations

    Natural Language Supervision for General-Purpose Audio Representations

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Improving Joint Speech-Text Representations Without Alignment

    Improving Joint Speech-Text Representations Without Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ AgentsAgents
  • MindAgent: Emergent Gaming Interaction

    MindAgent: Emergent Gaming Interaction

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • A Data Source for Reasoning Embodied Agents

    A Data Source for Reasoning Embodied Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • LASER: LLM Agent with State-Space Exploration for Web Navigation

    LASER: LLM Agent with State-Space Exploration for Web Navigation

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Agents: An Open-source Framework for Autonomous Language Agents

    Agents: An Open-source Framework for Autonomous Language Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

    ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

    BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ GamingGaming
  • MindAgent: Emergent Gaming Interaction

    MindAgent: Emergent Gaming Interaction

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
/ TransformersTransformers
  • Cure the headache of Transformers via Collinear Constrained Attention

    Cure the headache of Transformers via Collinear Constrained Attention

    Prof. Otto Nomos
    Prof. Otto NomosMay 27, 2024 ∙ 1 min read
  • Sparse Autoencoders Find Highly Interpretable Features in Language Models

    Sparse Autoencoders Find Highly Interpretable Features in Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Scaling Laws for Sparsely-Connected Foundation Models

    Scaling Laws for Sparsely-Connected Foundation Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Uncovering mesa-optimization algorithms in Transformers

    Uncovering mesa-optimization algorithms in Transformers

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Gated recurrent neural networks discover attention

    Gated recurrent neural networks discover attention

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • One Wide Feedforward is All You Need

    One Wide Feedforward is All You Need

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Vector Search with OpenAI Embeddings: Lucene Is All You Need

    Vector Search with OpenAI Embeddings: Lucene Is All You Need

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Bayesian Flow Networks

    Bayesian Flow Networks

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • YaRN: Efficient Context Window Extension of Large Language Models

    YaRN: Efficient Context Window Extension of Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models

    LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Composable Function-preserving Expansions for Transformer Architectures

    Composable Function-preserving Expansions for Transformer Architectures

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ Structured DataStructured Data
  • Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?

    Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • LMDX: Language Model-based Document Information Extraction and Localization

    LMDX: Language Model-based Document Information Extraction and Localization

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
/ PrivacyPrivacy
  •   Recovering from Privacy-Preserving Masking with Large Language Models

    Recovering from Privacy-Preserving Masking with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
/ EdgeEdge
  •   Recovering from Privacy-Preserving Masking with Large Language Models

    Recovering from Privacy-Preserving Masking with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
/ ChatChat
  • S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

    S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • Investigating Answerability of LLMs for Long-Form Question Answering

    Investigating Answerability of LLMs for Long-Form Question Answering

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • SoTaNa: The Open-Source Software Development Assistant

    SoTaNa: The Open-Source Software Development Assistant

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • PIPPA: A Partially Synthetic Conversational Dataset

    PIPPA: A Partially Synthetic Conversational Dataset

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ AudioAudio
  • Augmenting text for spoken language understanding with Large Language Models

    Augmenting text for spoken language understanding with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • Natural Language Supervision for General-Purpose Audio Representations

    Natural Language Supervision for General-Purpose Audio Representations

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Improving Joint Speech-Text Representations Without Alignment

    Improving Joint Speech-Text Representations Without Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ CompressionCompression
  • Language Modeling Is Compression

    Language Modeling Is Compression

    Prof. Otto Nomos
    Prof. Otto NomosMay 25, 2024 ∙ 1 min read
  • A Survey on Model Compression for Large Language Models

    A Survey on Model Compression for Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ RLHFRLHF
  • Stabilizing RLHF through Advantage Model and Selective Rehearsal

    Stabilizing RLHF through Advantage Model and Selective Rehearsal

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • Statistical Rejection Sampling Improves Preference Optimization

    Statistical Rejection Sampling Improves Preference Optimization

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Efficient RLHF: Reducing the Memory Usage of PPO

    Efficient RLHF: Reducing the Memory Usage of PPO

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]

    Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

    RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ HallucinationHallucination
  • Chain-of-Verification Reduces Hallucination in Large Language Models

    Chain-of-Verification Reduces Hallucination in Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • LMDX: Language Model-based Document Information Extraction and Localization

    LMDX: Language Model-based Document Information Extraction and Localization

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
/ EntityEntity
  • LMDX: Language Model-based Document Information Extraction and Localization

    LMDX: Language Model-based Document Information Extraction and Localization

    Prof. Otto Nomos
    Prof. Otto NomosMay 24, 2024 ∙ 1 min read
  • Leveraging Contextual Information for Effective Entity Salience Detection

    Leveraging Contextual Information for Effective Entity Salience Detection

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
/ DataData
  •   SlimPajama-DC: Understanding Data Combinations for LLM Training

    SlimPajama-DC: Understanding Data Combinations for LLM Training

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

    CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • A Data Source for Reasoning Embodied Agents

    A Data Source for Reasoning Embodied Agents

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

    When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • PIPPA: A Partially Synthetic Conversational Dataset

    PIPPA: A Partially Synthetic Conversational Dataset

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Shepherd: A Critic for Language Model Generation

    Shepherd: A Critic for Language Model Generation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ ReasoningReasoning
  • Contrastive Decoding Improves Reasoning in Large Language Models

    Contrastive Decoding Improves Reasoning in Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • Graph of Thoughts: Solving Elaborate Problems with Large Language Models

    Graph of Thoughts: Solving Elaborate Problems with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ InterpretabilityInterpretability
  • Sparse Autoencoders Find Highly Interpretable Features in Language Models

    Sparse Autoencoders Find Highly Interpretable Features in Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
/ TrainingTraining
  • Scaling Laws for Sparsely-Connected Foundation Models

    Scaling Laws for Sparsely-Connected Foundation Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

    From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Shepherd: A Critic for Language Model Generation

    Shepherd: A Critic for Language Model Generation

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ In-Context LearningIn-Context Learning
  • Ambiguity-Aware In-Context Learning with Large Language Models

    Ambiguity-Aware In-Context Learning with Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning

    FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

    RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • CausalLM is not optimal for in-context learning

    CausalLM is not optimal for in-context learning

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ EvaluationEvaluation
  • Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?

    Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

    The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ SummarizationSummarization
  • Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

    Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
  • DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

    DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

    From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
/ Reinforcement LearningReinforcement Learning
  • Statistical Rejection Sampling Improves Preference Optimization

    Statistical Rejection Sampling Improves Preference Optimization

    Prof. Otto Nomos
    Prof. Otto NomosOct 04, 2023 ∙ 1 min read
/ CodeCode
  • Large Language Models for Compiler Optimization

    Large Language Models for Compiler Optimization

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • LLM As DBA

    LLM As DBA

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

    BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Can Programming Languages Boost Each Other via Instruction Tuning?

    Can Programming Languages Boost Each Other via Instruction Tuning?

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • SoTaNa: The Open-Source Software Development Assistant

    SoTaNa: The Open-Source Software Development Assistant

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

    Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • OctoPack: Instruction Tuning Code Large Language Models

    OctoPack: Instruction Tuning Code Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Enhancing Network Management Using Code Generated by Large Language Models

    Enhancing Network Management Using Code Generated by Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ ScienceScience
  • AstroLLaMA: Towards Specialized Foundation Models in Astronomy

    AstroLLaMA: Towards Specialized Foundation Models in Astronomy

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • Large Language Model for Science: A Study on P vs. NP

    Large Language Model for Science: A Study on P vs. NP

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

    PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ MathMath
  • Large Language Model for Science: A Study on P vs. NP

    Large Language Model for Science: A Study on P vs. NP

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • GPT Can Solve Mathematical Problems Without a Calculator

    GPT Can Solve Mathematical Problems Without a Calculator

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
/ Open SourceOpen Source
  • Textbooks Are All You Need II: phi-1.5 technical report

    Textbooks Are All You Need II: phi-1.5 technical report

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • XGen-7B Technical Report

    XGen-7B Technical Report

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
/ ImageImage
  • StyleAdapter: A Single-Pass LoRA-Free Model for Stylized Image Generation

    StyleAdapter: A Single-Pass LoRA-Free Model for Stylized Image Generation

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • FLIRT: Feedback Loop In-context Red Teaming

    FLIRT: Feedback Loop In-context Red Teaming

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ LORALORA
  • StyleAdapter: A Single-Pass LoRA-Free Model for Stylized Image Generation

    StyleAdapter: A Single-Pass LoRA-Free Model for Stylized Image Generation

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]

    LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Platypus: Quick, Cheap, and Powerful Refinement of LLMs

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ ToolsTools
  • ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

    ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 03, 2023 ∙ 1 min read
  • ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]

    ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

    FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ SummarySummary
  • Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]

    Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Llama 2: Open Foundation and Fine-Tuned Chat Models [Commentary]

    Llama 2: Open Foundation and Fine-Tuned Chat Models [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Challenges and Applications of Large Language Models [Summary]

    Challenges and Applications of Large Language Models [Summary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ CommentaryCommentary
  • LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]

    LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]

    ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ SurveySurvey
  • A Survey on Model Compression for Large Language Models

    A Survey on Model Compression for Large Language Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ AlignmentAlignment
  • From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

    From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • Simple synthetic data reduces sycophancy in large language models

    Simple synthetic data reduces sycophancy in large language models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ ClimateClimate
  • WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ PersonalizationPersonalization
  • Teach LLMs to Personalize -- An Approach inspired by Writing Education

    Teach LLMs to Personalize -- An Approach inspired by Writing Education

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ DiffusionDiffusion
  • PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

    PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
  • FLIRT: Feedback Loop In-context Red Teaming

    FLIRT: Feedback Loop In-context Red Teaming

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ InferenceInference
  • Accelerating LLM Inference with Staged Speculative Decoding

    Accelerating LLM Inference with Staged Speculative Decoding

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read
/ SafetySafety
  • FLIRT: Feedback Loop In-context Red Teaming

    FLIRT: Feedback Loop In-context Red Teaming

    Prof. Otto Nomos
    Prof. Otto NomosOct 02, 2023 ∙ 1 min read