Multimodal Reasoning
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Benchmarks
Most implemented
OneEmo: A Unified Multimodal Reasoning Model for Emotion Perception, Understanding, and Interaction
DeAR: Decentralized Agentic Reasoning via Capability Grounding and Collaborative Thought Navigation
Heterogeneous Vision-Language Ensemble with Disagreement-Aware Reranking for Text-Based Person Anomaly Retrieval
ChartGalaxy: A Dataset for Infographic Chart Understanding and Generation
WebQA: Multihop and Multimodal QA
Papers
PhysVista: Benchmarking Physical Intelligence in VLMs via a Perception-Reasoning-Assessment Loop
Vision-Language Models (VLMs) have shown strong multimodal reasoning capabilities, yet whether they truly capture the physical consistency underlying real-world dynamics remains unclear. Existing benchmark paradigms ofte…
Multimodal ReasoningCan We Trust the Teacher? Decoupled Credit Direction-Magnitude for Self-Distillation
RLVR provides reliable trajectory-level credit, while OPSD offers dense supervision for token-level credit. This exposes a fundamental coupling when updating step-level credit direction and magnitude with teacher supervi…
Mathematical ReasoningMultimodal ReasoningNavHarness: Towards Lifelong Embodied Navigation
Frontier models can now perform well on individual embodied navigation tasks through multi-round multimodal reasoning with simple tools. Across successive tasks, however, an agent must also rely on an evolving map and ea…
Multimodal ReasoningWhat Do Hallucinations Reveal About Multimodal Reasoning? Diagnosing Visual Grounding Failures via Contrastive Decoding Probes
When strong multimodal models are widely available, progress requires new scientific methodologies beyond benchmark scores---using models as instruments for understanding behavior. We address this by asking: can we use l…
Multimodal ReasoningVisual GroundingReason Through the Latent! Making Latent Visual Reasoning Necessary
Latent visual reasoning aims to perform multimodal reasoning through hidden-state computation rather than explicit textual chains of thought. However, visual information being present in a latent state does not imply tha…
Multimodal ReasoningVisual ReasoningMobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control
Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on mobile robots, due to the persistent gap between high-level semanti…
Reinforcement LearningInstruction FollowingMultimodal ReasoningDecision Making