8 papers
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…
Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve Framework
Jundong Xu, Hao Fei, Meng Luo +6
In the context of large language models (LLMs), current advanced reasoning methods have made impressive strides in various reasoning tasks. However, when it comes to logical reason…
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…