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From the 1 of 15 linked papers with an AI index.

collaborators

15 papers

cs.CV2026

SLVMBench: Skill Learning from Video Memory

Yudong Yang, Guangzhi Sun, Yixuan Li +1

The paper presents SLVMBench, a benchmark that tests whether video large language models can learn procedural skills from multi‑hour video streams and then use that knowledge to an…

cs.CV2026

video-SALMONN-R: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding

Yixuan Li, Guangzhi Sun, Yudong Yang +1

Video large language models (LLMs) are often constrained by computation and memory budgets, leading them to use reduced frame rates and spatial resolutions, which may cause them to…

cs.AI2026

OmniMem: Perturbation-aware Memory Compression for Streaming Audio-Visual LLMs

Guangzhi Sun, Yixuan Li, Yudong Yang +1

Audio-visual large language models (LLMs) hold strong promise for long-form video understanding, yet their long-video inference is fundamentally limited by the linear growth of vid…

cs.SD2026

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection

Hangbin Yu, Yudong Yang, Rongfeng Su +2

Automatic depression detection using speech signals with acoustic and textual modalities is a promising approach for early diagnosis. Depression-related patterns exhibit sparsity i…

cs.SD2026

From Speech to Profile: A Protocol-Driven LLM Agent for Psychological Profile Generation

Xingjian Yang, Yudong Yang, Zhixing Guo +3

The psychological profile that structurally documents the case of a depression patient is essential for psychotherapy. Large language models can be applied to summarize the profile…

cs.SD2026

Speech-Audio Compositional Attacks on Multimodal LLMs and Their Mitigation with SALMONN-Guard

Yudong Yang, Xuezhen Zhang, Zhifeng Han +6

Recent progress in LLMs has enabled understanding of audio signals, but has also exposed new safety risks arising from complex audio inputs that are inadequately handled by current…