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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2411.15124
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Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 18 -
Large Language Models Are Human-Level Prompt Engineers
Paper • 2211.01910 • Published • 1 -
Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 43 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3
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Learning to Reason without External Rewards
Paper • 2505.19590 • Published • 29 -
Scalable Best-of-N Selection for Large Language Models via Self-Certainty
Paper • 2502.18581 • Published -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 90 -
Fractured Chain-of-Thought Reasoning
Paper • 2505.12992 • Published • 23
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2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings
Paper • 2501.01257 • Published • 52 -
Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models
Paper • 2501.01423 • Published • 44 -
REDUCIO! Generating 1024times1024 Video within 16 Seconds using Extremely Compressed Motion Latents
Paper • 2411.13552 • Published
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Video Creation by Demonstration
Paper • 2412.09551 • Published • 9 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 48 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 72 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38
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OpenThoughts: Data Recipes for Reasoning Models
Paper • 2506.04178 • Published • 48 -
Exploring Multi-Grained Concept Annotations for Multimodal Large Language Models
Paper • 2412.05939 • Published • 16 -
TÜLU 3: Pushing Frontiers in Open Language Model Post-Training
Paper • 2411.15124 • Published • 67 -
PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding
Paper • 2504.13180 • Published • 19
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Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 71 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104 -
argilla/magpie-ultra-v1.0
Viewer • Updated • 3.22M • 1.94k • 50 -
simplescaling/s1K-1.1
Viewer • Updated • 1k • 2.41k • 140
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
OpenThoughts: Data Recipes for Reasoning Models
Paper • 2506.04178 • Published • 48 -
Exploring Multi-Grained Concept Annotations for Multimodal Large Language Models
Paper • 2412.05939 • Published • 16 -
TÜLU 3: Pushing Frontiers in Open Language Model Post-Training
Paper • 2411.15124 • Published • 67 -
PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding
Paper • 2504.13180 • Published • 19
-
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 18 -
Large Language Models Are Human-Level Prompt Engineers
Paper • 2211.01910 • Published • 1 -
Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 43 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3
-
Learning to Reason without External Rewards
Paper • 2505.19590 • Published • 29 -
Scalable Best-of-N Selection for Large Language Models via Self-Certainty
Paper • 2502.18581 • Published -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 90 -
Fractured Chain-of-Thought Reasoning
Paper • 2505.12992 • Published • 23
-
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Paper • 2406.08464 • Published • 71 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104 -
argilla/magpie-ultra-v1.0
Viewer • Updated • 3.22M • 1.94k • 50 -
simplescaling/s1K-1.1
Viewer • Updated • 1k • 2.41k • 140
-
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings
Paper • 2501.01257 • Published • 52 -
Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models
Paper • 2501.01423 • Published • 44 -
REDUCIO! Generating 1024times1024 Video within 16 Seconds using Extremely Compressed Motion Latents
Paper • 2411.13552 • Published
-
Video Creation by Demonstration
Paper • 2412.09551 • Published • 9 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 48 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 72 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38