Collection by
Jul 2, 2024
Jul 2, 2024Collections
Discover the best community collections!
Collections including paper arxiv:2406.20094
Collection by
Jan 10
Jan 10-
RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 71 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 132 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90
Collection by
12 days ago
12 days ago-
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 16 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
Collection by
Sep 26
Sep 26-
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Paper • 2310.04406 • Published • 10 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 14 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 50 -
Voyager: An Open-Ended Embodied Agent with Large Language Models
Paper • 2305.16291 • Published • 11
Collection by
Sep 16
Sep 16-
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 55 -
FlowMind: Automatic Workflow Generation with LLMs
Paper • 2404.13050 • Published • 34 -
How Far Can We Go with Practical Function-Level Program Repair?
Paper • 2404.12833 • Published • 7 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 71
Collection by
Sep 4, 2024
Sep 4, 2024-
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31 -
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries
Paper • 2406.12824 • Published • 21 -
Tokenization Falling Short: The Curse of Tokenization
Paper • 2406.11687 • Published • 16 -
Iterative Length-Regularized Direct Preference Optimization: A Case Study on Improving 7B Language Models to GPT-4 Level
Paper • 2406.11817 • Published • 13
Collection by
Aug 17, 2024
Aug 17, 2024-
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity
Paper • 2305.13169 • Published • 3 -
A Survey on Data Selection for Language Models
Paper • 2402.16827 • Published • 4 -
HuggingFaceFW/fineweb-edu
Viewer • Updated • 3.5B • 238k • 828 -
allenai/MADLAD-400
Updated • 33.2k • 152
Collection by
Jul 23, 2024
Jul 23, 2024-
Iterative Reasoning Preference Optimization
Paper • 2404.19733 • Published • 49 -
Better & Faster Large Language Models via Multi-token Prediction
Paper • 2404.19737 • Published • 80 -
ORPO: Monolithic Preference Optimization without Reference Model
Paper • 2403.07691 • Published • 70 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 115
Collection by
Sep 26
Sep 26-
Training Software Engineering Agents and Verifiers with SWE-Gym
Paper • 2412.21139 • Published • 24 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 48 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 117
Collection by
Jun 19
Jun 19Collection by
Jul 2, 2024
Jul 2, 2024Collection by
Sep 4, 2024
Sep 4, 2024-
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31 -
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries
Paper • 2406.12824 • Published • 21 -
Tokenization Falling Short: The Curse of Tokenization
Paper • 2406.11687 • Published • 16 -
Iterative Length-Regularized Direct Preference Optimization: A Case Study on Improving 7B Language Models to GPT-4 Level
Paper • 2406.11817 • Published • 13
Collection by
Jan 10
Jan 10-
RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 71 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 132 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90
Collection by
Aug 17, 2024
Aug 17, 2024-
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity
Paper • 2305.13169 • Published • 3 -
A Survey on Data Selection for Language Models
Paper • 2402.16827 • Published • 4 -
HuggingFaceFW/fineweb-edu
Viewer • Updated • 3.5B • 238k • 828 -
allenai/MADLAD-400
Updated • 33.2k • 152
Collection by
12 days ago
12 days ago-
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 16 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
Collection by
Jul 23, 2024
Jul 23, 2024-
Iterative Reasoning Preference Optimization
Paper • 2404.19733 • Published • 49 -
Better & Faster Large Language Models via Multi-token Prediction
Paper • 2404.19737 • Published • 80 -
ORPO: Monolithic Preference Optimization without Reference Model
Paper • 2403.07691 • Published • 70 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 115
Collection by
Sep 26
Sep 26-
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Paper • 2310.04406 • Published • 10 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 14 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 50 -
Voyager: An Open-Ended Embodied Agent with Large Language Models
Paper • 2305.16291 • Published • 11
Collection by
Sep 26
Sep 26-
Training Software Engineering Agents and Verifiers with SWE-Gym
Paper • 2412.21139 • Published • 24 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 48 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 117
Collection by
Sep 16
Sep 16-
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 55 -
FlowMind: Automatic Workflow Generation with LLMs
Paper • 2404.13050 • Published • 34 -
How Far Can We Go with Practical Function-Level Program Repair?
Paper • 2404.12833 • Published • 7 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 71
Collection by
Jun 19
Jun 19