5 papers · 1 filter
Pause and Think: A Dataset and Benchmark for Video-Grounded Assistive Action Suggestion
Shivam Singh, Saptarshi Majumder, Pratik Prabhanjan Brahma +2
Recent Vision-Language Models (VLMs) struggle with grounded reasoning, temporal consistency, and context aware planning in videos. We introduce pause-and-think-T, a reasoning-centr…
DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking
Akash Haridas, Utkarsh Saxena, Parsa Ashrafi Fashi +3
Diffusion Transformers rely on static patchify tokenization, assigning the same token budget to smooth backgrounds, detailed object regions, noisy early timesteps, and late-stage r…
Ego-InBetween: Generating Object State Transitions in Ego-Centric Videos
Mengmeng Ge, Takashi Isobe, Xu Jia +7
Understanding physical transformation processes is crucial for both human cognition and artificial intelligence systems, particularly from an egocentric perspective, which serves a…
DUET-VLM: Dual stage Unified Efficient Token reduction for VLM Training and Inference
Aditya Kumar Singh, Hitesh Kandala, Pratik Prabhanjan Brahma +2
Vision-language models (VLMs) have achieved remarkable multimodal understanding and reasoning capabilities, yet remain computationally expensive due to dense visual tokenization. E…
VideoSeek: Long-Horizon Video Agent with Tool-Guided Seeking
Jingyang Lin, Jialian Wu, Jiang Liu +6
Video agentic models have advanced challenging video-language tasks. However, most agentic approaches still heavily rely on greedy parsing over densely sampled video frames, result…