collaborators

9 papers

cs.LG2026

Diagnosing and Mitigating Perception-Decision Misalignment in Omni-LLMs via Modality Subspace Activation

Hongbo Jiang, Jie Li, Yunhang Shen +2

Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, their strong performance often m…

cs.CV2026

WaveZip: Wavelet-Driven Space-Time Decoupling for Video Token Condensation

Yuhui Zeng, Wang Chen, Jinfa Huang +5

Existing Large Vision-Language Models (LVLMs) struggle with long-form video understanding due to the quadratic computational cost of visual tokens. While recent efficient methods a…

cs.AI2026

SocialOmni: Benchmarking Audio-Visual Social Interactivity in Omni Models

Tianyu Xie, Jinfa Huang, Yuexiao Ma +11

Omni-modal large language models (OLMs) redefine human-machine interaction by natively integrating audio, vision, and text. However, existing OLM benchmarks remain anchored to stat…

cs.CL2026

Training-Free Multimodal Large Language Model Orchestration

Tianyu Xie, Yuexiao Ma, Yuhang Wu +5

Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantial data and compute costs and lim…

cs.AI2026

A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation

Qingchuan Ma, Yuexiao Ma, Yongkang Xie +3

Abstract reasoning ability reflects the intelligence and generalization capacity of LLMs to extract and apply abstract rules. However, accurately measuring this ability remains cha…

cs.CV2026

Wavelet-based Frame Selection by Detecting Semantic Boundary for Long Video Understanding

Wang Chen, Yuhui Zeng, Yongdong Luo +5

Frame selection is crucial due to high frame redundancy and limited context windows when applying Large Vision-Language Models (LVLMs) to long videos. Current methods typically sel…