11 citations · 47 across the 66 of their papers we have counts for
17 papers · 1 filter
Evidence-Backed Video Question Answering
Shijie Wang, Honglu Zhou, Ziyang Wang +5
Current Video Large Language Models (Video LLMs) excel in question answering (QA) but largely operate as black boxes, providing textual answers without verifiable visual grounding.…
Future Optical Flow Prediction Improves Robot Control & Video Generation
Kanchana Ranasinghe, Honglu Zhou, Yu Fang +7
Future motion representations, such as optical flow, offer immense value for control and generative tasks. However, forecasting generalizable spatially dense motion representations…
Active Video Perception: Iterative Evidence Seeking for Agentic Long Video Understanding
Ziyang Wang, Honglu Zhou, Shijie Wang +6
Long video understanding (LVU) is challenging because answering real-world queries often depends on sparse, temporally dispersed cues buried in hours of mostly redundant and irrele…
BLIP3o-NEXT: Next Frontier of Native Image Generation
Jiuhai Chen, Le Xue, Zhiyang Xu +12
We present BLIP3o-NEXT, a fully open-source foundation model in the BLIP3 series that advances the next frontier of native image generation. BLIP3o-NEXT unifies text-to-image gener…
WALT: Web Agents that Learn Tools
Viraj Prabhu, Yutong Dai, Matthew Fernandez +8
Web agents promise to automate complex browser tasks, but current methods remain brittle -- relying on step-by-step UI interactions and heavy LLM reasoning that break under dynamic…
Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data
Honglu Zhou, Xiangyu Peng, Shrikant Kendre +4
Next-generation AI companions must go beyond general video understanding to resolve spatial and temporal references in dynamic, real-world environments. Existing Video Large Langua…