7 papers
ReCALL: Recalibrating Capability Degradation for MLLM-based Composed Image Retrieval
Tianyu Yang, Chenwei He, Xiangzhao Hao +6
Composed Image Retrieval (CIR) aims to retrieve target images based on a hybrid query comprising a reference image and a modification text. Early dual-tower Vision-Language Models…
The Missing Half: Unveiling Training-time Implicit Safety Risks Beyond Deployment
Zhexin Zhang, Yida Lu, Junfeng Fang +8
Safety risks of AI models have been widely studied at deployment time, such as jailbreak attacks that elicit harmful outputs. In contrast, safety risks emerging during training rem…
Towards Comprehensive Stage-wise Benchmarking of Large Language Models in Fact-Checking
Hongzhan Lin, Zixin Chen, Zhiqi Shen +5
Large Language Models (LLMs) are increasingly deployed in real-world fact-checking systems, yet existing evaluations focus predominantly on claim verification and overlook the broa…
Thinking with Blueprints: Assisting Vision-Language Models in Spatial Reasoning via Structured Object Representation
Weijian Ma, Shizhao Sun, Tianyu Yu +3
Spatial reasoning -- the ability to perceive and reason about relationships in space -- advances vision-language models (VLMs) from visual perception toward spatial semantic unders…
EQ-TAA: Equivariant Traffic Accident Anticipation via Diffusion-Based Accident Video Synthesis
Jianwu Fang, Lei-Lei Li, Zhedong Zheng +4
Traffic Accident Anticipation (TAA) in traffic scenes is a challenging problem for achieving zero fatalities in the future. Current approaches typically treat TAA as a supervised l…
Understanding Long Videos via LLM-Powered Entity Relation Graphs
Meng Chu, Yicong Li, Tat-Seng Chua
The analysis of extended video content poses unique challenges in artificial intelligence, particularly when dealing with the complexity of tracking and understanding visual elemen…