most citedExploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.SD2026

SonicBench: Dissecting the Physical Perception Bottleneck in Large Audio Language Models

Yirong Sun, Yanjun Chen, Xin Qiu +8

Large Audio Language Models (LALMs) excel at semantic and paralinguistic tasks, yet their ability to perceive the fundamental physical attributes of audio such as pitch, loudness,…

cs.CV2026

PhysVideoGenerator: Towards Physically Aware Video Generation via Latent Physics Guidance

Siddarth Nilol Kundur Satish, Devesh Jaiswal, Hongyu Chen +1

Current video generation models produce high-quality aesthetic videos but often struggle to learn representations of real-world physics dynamics, resulting in artifacts such as unn…

cs.SD2025

BRACE: A Benchmark for Robust Audio Caption Quality Evaluation

Tianyu Guo, Hongyu Chen, Hao Liang +5

Automatic audio captioning is essential for audio understanding, enabling applications such as accessibility and content indexing. However, evaluating the quality of audio captions…

cs.CV2025

UML-CoT: Structured Reasoning and Planning with Unified Modeling Language for Robotic Room Cleaning

Hongyu Chen, Guangrun Wang

Chain-of-Thought (CoT) prompting improves reasoning in large language models (LLMs), but its reliance on unstructured text limits interpretability and executability in embodied tas…

cs.CV20251 cited

Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Hongcheng Gao, Jiashu Qu, Jingyi Tang +6

The hallucination of large multimodal models (LMMs), providing responses that appear correct but are actually incorrect, limits their reliability and applicability. This paper aims…

cs.CL2025

Efficient Inference for Large Reasoning Models: A Survey

Yue Liu, Jiaying Wu, Yufei He +11

Large Reasoning Models (LRMs) significantly improve the reasoning ability of Large Language Models (LLMs) by learning to reason, exhibiting promising performance in solving complex…