14 papers
DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition
Hanjun Luo, Yingbin Jin, Xinfeng Li +6
The advancements of Large Language Models (LLMs) have spurred a growing interest in their application to Named Entity Recognition (NER) methods. However, existing datasets are prim…
BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models
Hanjun Luo, Zhimu Huang, Haoyu Huang +5
Text-to-Image (T2I) generative models have revolutionized content creation, yet they inherently risk amplifying societal biases. While sociological research provides systematic cla…
Towards Proactive Personalization through Profile Customization for Individual Users in Dialogues
Xiaotian Zhang, Yuan Wang, Ruizhe Chen +3
The deployment of Large Language Models (LLMs) in interactive systems necessitates a deep alignment with the nuanced and dynamic preferences of individual users. Current alignment…
Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning
Ruizhe Chen, Zhiting Fan, Tianze Luo +7
Video Temporal Grounding (VTG) aims to localize relevant temporal segments in videos given natural language queries. Despite recent progress with large vision-language models (LVLM…
Med-U1: Incentivizing Unified Medical Reasoning in LLMs via Large-scale Reinforcement Learning
Xiaotian Zhang, Yuan Wang, Zhaopeng Feng +6
Medical Question-Answering (QA) encompasses a broad spectrum of tasks, including multiple choice questions (MCQ), open-ended text generation, and complex computational reasoning. D…
CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making
Songtao Jiang, Yuan Wang, Ruizhe Chen +8
In medical visual question answering (Med-VQA), achieving accurate responses relies on three critical steps: precise perception of medical imaging data, logical reasoning grounded…