11 citations · 14 across the 8 of their papers we have counts for
9 papers
Pierce the Mists, Greet the Sky: Decipher Knowledge Overshadowing via Knowledge Circuit Analysis
Haoming Huang, Yibo Yan, Jiahao Huo +4
Large Language Models (LLMs), despite their remarkable capabilities, are hampered by hallucinations. A particularly challenging variant, knowledge overshadowing, occurs when one pi…
Aligning Multimodal LLM with Human Preference: A Survey
Tao Yu, Yi-Fan Zhang, Chaoyou Fu +14
Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs),…
Position: LLMs Can be Good Tutors in English Education
Jingheng Ye, Shen Wang, Deqing Zou +8
While recent efforts have begun integrating large language models (LLMs) into English education, they often rely on traditional approaches to learning tasks without fully embracing…
Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey
Yunkai Dang, Kaichen Huang, Jiahao Huo +11
The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV) systems driving advancements in…
A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges
Yibo Yan, Jiamin Su, Jianxiang He +7
Mathematical reasoning, a core aspect of human cognition, is vital across many domains, from educational problem-solving to scientific advancements. As artificial general intellige…
Optimizing Multispectral Object Detection: A Bag of Tricks and Comprehensive Benchmarks
Chen Zhou, Peng Cheng, Junfeng Fang +6
Multispectral object detection, utilizing RGB and TIR (thermal infrared) modalities, is widely recognized as a challenging task. It requires not only the effective extraction of fe…
MINER: Mining the Underlying Pattern of Modality-Specific Neurons in Multimodal Large Language Models
Kaichen Huang, Jiahao Huo, Yibo Yan +3
In recent years, multimodal large language models (MLLMs) have significantly advanced, integrating more modalities into diverse applications. However, the lack of explainability re…
Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality
Guanyu Zhou, Yibo Yan, Xin Zou +3
Multimodal Large Language Models (MLLMs) have emerged as a central focus in both industry and academia, but often suffer from biases introduced by visual and language priors, which…
ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection
Yibo Yan, Shen Wang, Jiahao Huo +13
As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particularly promising, especially in addr…