4 papers
OmniHalluc-L: Counterfactual Benchmarking and Modality-Perturbation Reliability Calibration for Long-Form Omni Hallucination
Zixuan Dong, Jiafu Tang, Zhide Lei +7
Long-video Omni assistants often fail not by inventing content, but by misbinding real evidence: they hear the right utterance and see the right event, yet attach it to the wrong s…
LiViBench: An Omnimodal Benchmark for Interactive Livestream Video Understanding
Xiaodong Wang, Langling Huang, Zhirong Wu +4
The development of multimodal large language models (MLLMs) has advanced general video understanding. However, existing video evaluation benchmarks primarily focus on non-interacti…
LeanPO: Lean Preference Optimization for Likelihood Alignment in Video-LLMs
Xiaodong Wang, Jinfa Huang, Li Yuan +1
Most Video Large Language Models (Video-LLMs) adopt preference alignment techniques, e.g., DPO~\citep{rafailov2024dpo}, to optimize the reward margin between a winning response ($y…
ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos
Xiaodong Wang, Peixi Peng
Real-world driving requires people to observe the current environment, anticipate the future, and make appropriate driving decisions. This requirement is aligned well with the capa…