V-ICAL Bench: Evaluating Video In-Context Learning for Multimodal Agents in Interactive Environments
cs.CV
Submitted: 2026-09-14
Updated: 2026-10-09
Code: https://github.com/VisionXLab/V-ICAL
Project page: https://visionxlab.github.io/V-ICAL-Homepage
Terminology
Sources
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- Demo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition
- Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding
- Benchmarking the Spectrum of Agent Capabilities
- Many-Shot In-Context Learning in Multimodal Foundation Models
- Learning Adaptive and Temporally Causal Video Tokenization in a 1D Latent Space
- MM-WebAgent: A Hierarchical Multimodal Web Agent for Webpage Generation
- RISE-Video: Can Video Generators Decode Implicit World Rules?
- Moment-Video: Diagnosing Temporal Fidelity of Video MLLMs on Momentary Visual Events
- GameWorld: Towards Standardized and Verifiable Evaluation of Multimodal Game Agents
- LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
- Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity
- Gemma 4 Technical Report
- Kimi K3: Open Frontier Intelligence
- GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
- Atari-GPT: Benchmarking Multimodal Large Language Models as Low-Level Policies in Atari Games
- MiMo-VL Technical Report
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
- Qwen3-Omni Technical Report
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