6 papers · 1 filter
No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs
Haojian Huang, Harold Haodong Chen, Meng Luo +6
We introduce VidPair-Halluc, a new benchmark for evaluating video hallucination in large video models (LVMs) under rigorous and controlled conditions. Unlike previous benchmarks th…
Unveiling the Cognitive Compass: Theory-of-Mind-Guided Multimodal Emotion Reasoning
Meng Luo, Bobo Li, Shanqing Xu +8
Despite rapid progress in multimodal large language models (MLLMs), their capability for deep emotional understanding remains limited. We argue that genuine affective intelligence…
Video-HOCA: A Diagnostic Benchmark for Physical Anomaly Reasoning in Video-LLMs
Chang Liu, Yunfan Ye, Qingyang Zhou +5
We introduce Video-HOCA, a diagnostic benchmark for physical anomaly reasoning in videos. Video-HOCA uses an Ontological-Causal taxonomy to distinguish violations of an entity's ow…
Dr.V: A Hierarchical Perception-Temporal-Cognition Framework to Diagnose Video Hallucination by Fine-grained Spatial-Temporal Grounding
Meng Luo, Shengqiong Wu, Liqiang Jing +12
Recent advancements in large video models (LVMs) have significantly enhance video understanding. However, these models continue to suffer from hallucinations, producing content tha…
On Path to Multimodal Generalist: General-Level and General-Bench
Hao Fei, Yuan Zhou, Juncheng Li +29
The Multimodal Large Language Model (MLLM) is currently experiencing rapid growth, driven by the advanced capabilities of LLMs. Unlike earlier specialists, existing MLLMs are evolv…
VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models
Haojian Huang, Haodong Chen, Shengqiong Wu +5
Large Video Models (LVMs) built upon Large Language Models (LLMs) have shown promise in video understanding but often suffer from misalignment with human intuition and video halluc…