9 citations · 20 across the 18 of their papers we have counts for
6 papers · 2 filters
Think Globally, Group Locally: Evaluating LLMs Using Multi-Lingual Word Grouping Games
César Guerra-Solano, Zhuochun Li, Xiang Lorraine Li
Large language models (LLMs) can exhibit biases in reasoning capabilities due to linguistic modality, performing better on tasks in one language versus another, even with similar c…
MMBERT: Scaled Mixture-of-Experts Multimodal BERT for Robust Chinese Hate Speech Detection under Cloaking Perturbations
Qiyao Xue, Yuchen Dou, Ryan Shi +2
Hate speech detection on Chinese social networks presents distinct challenges, particularly due to the widespread use of cloaking techniques designed to evade conventional text-bas…
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
Juncheng Wu, Wenlong Deng, Xingxuan Li +12
Medical tasks such as diagnosis and treatment planning require precise and complex reasoning, particularly in life-critical domains. Unlike mathematical reasoning, medical reasonin…
Similarity-Based Domain Adaptation with LLMs
Jie He, Wendi Zhou, Xiang Lorraine Li +1
Unsupervised domain adaptation leverages abundant labeled data from various source domains to generalize onto unlabeled target data. Prior research has primarily focused on learnin…
SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models
Xianfu Cheng, Wei Zhang, Shiwei Zhang +16
The increasing application of multi-modal large language models (MLLMs) across various sectors have spotlighted the essence of their output reliability and accuracy, particularly t…
"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models
Jihao Gu, Yingyao Wang, Pi Bu +17
The evaluation of factual accuracy in large vision language models (LVLMs) has lagged behind their rapid development, making it challenging to fully reflect these models' knowledge…