-
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:2504.07096
-
R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Paper • 2503.10615 • Published • 17 -
UniGoal: Towards Universal Zero-shot Goal-oriented Navigation
Paper • 2503.10630 • Published • 6 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL
Paper • 2503.07536 • Published • 88
-
MLGym: A New Framework and Benchmark for Advancing AI Research Agents
Paper • 2502.14499 • Published • 192 -
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
Paper • 2502.14739 • Published • 104 -
How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?
Paper • 2502.14502 • Published • 91 -
PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
Paper • 2502.14282 • Published • 29
-
Latent Reasoning in LLMs as a Vocabulary-Space Superposition
Paper • 2510.15522 • Published • 1 -
Language Models are Injective and Hence Invertible
Paper • 2510.15511 • Published • 68 -
Eliciting Secret Knowledge from Language Models
Paper • 2510.01070 • Published • 4 -
Interpreting Language Models Through Concept Descriptions: A Survey
Paper • 2510.01048 • Published • 2
-
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Paper • 2508.06471 • Published • 192 -
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
Paper • 2508.14444 • Published • 38 -
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Paper • 2507.06261 • Published • 64 -
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper • 2506.13585 • Published • 273
-
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 85 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 56 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
-
Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 93 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 23 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 30
-
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 14 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 60 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 48
-
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
-
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Paper • 2508.06471 • Published • 192 -
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
Paper • 2508.14444 • Published • 38 -
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Paper • 2507.06261 • Published • 64 -
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper • 2506.13585 • Published • 273
-
R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Paper • 2503.10615 • Published • 17 -
UniGoal: Towards Universal Zero-shot Goal-oriented Navigation
Paper • 2503.10630 • Published • 6 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL
Paper • 2503.07536 • Published • 88
-
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 85 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 56 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
-
MLGym: A New Framework and Benchmark for Advancing AI Research Agents
Paper • 2502.14499 • Published • 192 -
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
Paper • 2502.14739 • Published • 104 -
How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?
Paper • 2502.14502 • Published • 91 -
PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
Paper • 2502.14282 • Published • 29
-
Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 93 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 23 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 30
-
Latent Reasoning in LLMs as a Vocabulary-Space Superposition
Paper • 2510.15522 • Published • 1 -
Language Models are Injective and Hence Invertible
Paper • 2510.15511 • Published • 68 -
Eliciting Secret Knowledge from Language Models
Paper • 2510.01070 • Published • 4 -
Interpreting Language Models Through Concept Descriptions: A Survey
Paper • 2510.01048 • Published • 2
-
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 14 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 60 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 48