-
Robust Multimodal Large Language Models Against Modality Conflict
Paper • 2507.07151 • Published • 5 -
One Token to Fool LLM-as-a-Judge
Paper • 2507.08794 • Published • 31 -
Test-Time Scaling with Reflective Generative Model
Paper • 2507.01951 • Published • 107 -
KV Cache Steering for Inducing Reasoning in Small Language Models
Paper • 2507.08799 • Published • 40
Collections
Discover the best community collections!
Collections including paper arxiv:2507.07151
-
Qwen2.5-Omni Technical Report
Paper • 2503.20215 • Published • 166 -
Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPO
Paper • 2505.22453 • Published • 46 -
UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning
Paper • 2505.23380 • Published • 22 -
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models
Paper • 2505.21523 • Published • 13
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 8.14k • 1.23k -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct
Text Generation • 8B • Updated • 138 • 15 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
-
Analyzing The Language of Visual Tokens
Paper • 2411.05001 • Published • 24 -
Large Multi-modal Models Can Interpret Features in Large Multi-modal Models
Paper • 2411.14982 • Published • 19 -
Rethinking Token Reduction in MLLMs: Towards a Unified Paradigm for Training-Free Acceleration
Paper • 2411.17686 • Published • 20 -
On the Limitations of Vision-Language Models in Understanding Image Transforms
Paper • 2503.09837 • Published • 10
-
Robust Multimodal Large Language Models Against Modality Conflict
Paper • 2507.07151 • Published • 5 -
One Token to Fool LLM-as-a-Judge
Paper • 2507.08794 • Published • 31 -
Test-Time Scaling with Reflective Generative Model
Paper • 2507.01951 • Published • 107 -
KV Cache Steering for Inducing Reasoning in Small Language Models
Paper • 2507.08799 • Published • 40
-
microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 8.14k • 1.23k -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct
Text Generation • 8B • Updated • 138 • 15 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
-
Qwen2.5-Omni Technical Report
Paper • 2503.20215 • Published • 166 -
Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPO
Paper • 2505.22453 • Published • 46 -
UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning
Paper • 2505.23380 • Published • 22 -
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models
Paper • 2505.21523 • Published • 13
-
Analyzing The Language of Visual Tokens
Paper • 2411.05001 • Published • 24 -
Large Multi-modal Models Can Interpret Features in Large Multi-modal Models
Paper • 2411.14982 • Published • 19 -
Rethinking Token Reduction in MLLMs: Towards a Unified Paradigm for Training-Free Acceleration
Paper • 2411.17686 • Published • 20 -
On the Limitations of Vision-Language Models in Understanding Image Transforms
Paper • 2503.09837 • Published • 10
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23