Collections
Discover the best community collections!
Collections including paper arxiv:2512.07461
-
Guided Self-Evolving LLMs with Minimal Human Supervision
Paper • 2512.02472 • Published • 55 -
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Paper • 2509.25454 • Published • 146 -
Video Reasoning without Training
Paper • 2510.17045 • Published • 8 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 273
-
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper • 2509.19284 • Published • 23 -
Soft Tokens, Hard Truths
Paper • 2509.19170 • Published • 16 -
CompLLM: Compression for Long Context Q&A
Paper • 2509.19228 • Published • 10 -
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
Paper • 2509.06861 • Published • 9
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 86 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 38 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 40 -
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Paper • 2310.08491 • Published • 57 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 37 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 25
-
Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning
Paper • 2512.07461 • Published • 78 -
RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling
Paper • 2506.08672 • Published • 30 -
ReflectEvo: Improving Meta Introspection of Small LLMs by Learning Self-Reflection
Paper • 2505.16475 • Published • 3
-
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
Paper • 2510.23587 • Published • 67 -
D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI
Paper • 2510.05684 • Published • 143 -
Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation
Paper • 2510.08673 • Published • 126 -
Lumine: An Open Recipe for Building Generalist Agents in 3D Open Worlds
Paper • 2511.08892 • Published • 210
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 277 -
SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis
Paper • 2506.02096 • Published • 52 -
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation
Paper • 2506.02397 • Published • 36 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 143
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
-
Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning
Paper • 2512.07461 • Published • 78 -
RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling
Paper • 2506.08672 • Published • 30 -
ReflectEvo: Improving Meta Introspection of Small LLMs by Learning Self-Reflection
Paper • 2505.16475 • Published • 3
-
Guided Self-Evolving LLMs with Minimal Human Supervision
Paper • 2512.02472 • Published • 55 -
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Paper • 2509.25454 • Published • 146 -
Video Reasoning without Training
Paper • 2510.17045 • Published • 8 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 273
-
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
Paper • 2510.23587 • Published • 67 -
D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI
Paper • 2510.05684 • Published • 143 -
Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation
Paper • 2510.08673 • Published • 126 -
Lumine: An Open Recipe for Building Generalist Agents in 3D Open Worlds
Paper • 2511.08892 • Published • 210
-
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper • 2509.19284 • Published • 23 -
Soft Tokens, Hard Truths
Paper • 2509.19170 • Published • 16 -
CompLLM: Compression for Long Context Q&A
Paper • 2509.19228 • Published • 10 -
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
Paper • 2509.06861 • Published • 9
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 277 -
SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis
Paper • 2506.02096 • Published • 52 -
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation
Paper • 2506.02397 • Published • 36 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 143
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 86 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 38 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
-
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 40 -
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Paper • 2310.08491 • Published • 57 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 37 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 25