1 citations · 1 across the 4 of their papers we have counts for
4 papers · 1 filter
Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context
Zhaowei Wang, Lishu Luo, Haodong Duan +9
Long-context modeling is becoming a core capability of modern large vision-language models (LVLMs), enabling sustained context management across long-document understanding, video…
SphereVAD: Training-Free Video Anomaly Detection via Geodesic Inference on the Unit Hypersphere
Chao Huang, Penfei Wei, Wei Wang +5
Video anomaly detection (VAD) aims to automatically identify events that deviate from normal patterns in untrimmed surveillance videos. Existing methods universally depend on large…
XModBench: Benchmarking Cross-Modal Capabilities and Consistency in Omni-Language Models
Xingrui Wang, Jiang Liu, Chao Huang +7
Omni-modal large language models (OLLMs) aim to unify audio, vision, and text understanding within a single framework. While existing benchmarks primarily evaluate general cross-mo…
DRIFT: Transferring Reasoning Priors for Efficient MLLM Fine-Tuning
Chao Huang, Zeliang Zhang, Jiang Liu +7
Multimodal large language models (MLLMs) have made rapid progress, yet their reasoning ability often lags behind strong text-only LLMs. Bridging this gap typically requires large-s…