GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?
cs.AI
Submitted: 2026-10-10
Updated: 2026-10-10
Code: https://github.com/SYSTRAN/faster-whisper
Sources
- Seamless Interaction: Dyadic Audiovisual Motion Modeling and Large-Scale Dataset
- Ming-Omni: A Unified Multimodal Model for Perception and Generation
- Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic
- Attention Alignment Between Humans and Vision-Language Models
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
- Dual Thinking and Logical Processing -- Are Multi-modal Large Language Models Closing the Gap with Human Vision ?
- Embodied AI Agents: Modeling the World
- Can MLLMs Read the Room? A Multimodal Benchmark for Verifying Truthfulness in Multi-Party Social Interactions
- AffectGPT: Dataset and Framework for Explainable Multimodal Emotion Recognition
- RoBERTa: A Robustly Optimized BERT Pretraining Approach
- MMBench: Is Your Multi-modal Model an All-around Player?
- Social Genome: Grounded Social Reasoning Abilities of Multimodal Models
- MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
- Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation
- Grad-CAM: Why did you say that?
- Gemma 4 Technical Report
- How Social is It? A Benchmark for LLMs' Capabilities in Multi-user Multi-turn Social Agent Tasks
- Qwen2.5-Omni Technical Report
- Qwen3-Omni Technical Report
- MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations
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