activity
20242026
collaborators

12 papers

cs.CV2026

Exploring Audio Hallucination in Egocentric Video Understanding

Ashish Seth, Xinhao Mei, Changsheng Zhao +9

Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly when visual information is unstab…

cs.LG2026

Neural Computers

Mingchen Zhuge, Changsheng Zhao, Haozhe Liu +16

We propose a new frontier: Neural Computers (NCs) that unify computation, memory, and I/O of traditional computers in a learned runtime state. Our long-term goal is the Completely…

cs.CV2026

Small Vision-Language Models are Smart Compressors for Long Video Understanding

Junjie Fei, Jun Chen, Zechun Liu +13

Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets and exacerbate the lost-in-the…

cs.CV2026

Efficient Universal Perception Encoder

Chenchen Zhu, Saksham Suri, Cijo Jose +8

Running AI models on smart edge devices can unlock versatile user experiences, but presents challenges due to limited compute and the need to handle multiple tasks simultaneously.…

cs.CV2026

EgoAVU: Egocentric Audio-Visual Understanding

Ashish Seth, Xinhao Mei, Changsheng Zhao +9

Understanding egocentric videos plays a vital role for embodied intelligence. Recent multi-modal large language models (MLLMs) can accept both visual and audio inputs. However, due…

cs.CV2026

VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice

Shuming Liu, Mingchen Zhuge, Changsheng Zhao +20

Chain-of-thought (CoT) reasoning has emerged as a powerful tool for multimodal large language models on video understanding tasks. However, its necessity and advantages over direct…