4 papers
Evaluating Test-Time Scaling LLMs for Legal Reasoning: OpenAI o1, DeepSeek-R1, and Beyond
Yinghao Hu, Yaoyao Yu, Leilei Gan +3
Recent advances in test-time scaling of large language models (LLMs), exemplified by DeepSeek-R1 and OpenAI's o1, show that extending the chain of thought during inference can sign…
MM-ARC: Multimodal Adaptive Routing of Capital with Robustness-Audited Strategy Pools
Yang Chen, Yueheng Jiang, Zhaozhao Ma +8
Financial trading systems must convert multimodal market history into executable positions while limiting overfitting from repeated strategy search. We introduce MM-ARC (MultiModal…
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering
Yinghao Hu, Leilei Gan, Wenyi Xiao +2
Hallucination, or the generation of incorrect or fabricated information, remains a critical challenge in large language models (LLMs), particularly in high-stake domains such as le…
Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback
Wenyi Xiao, Ziwei Huang, Leilei Gan +6
The rapidly developing Large Vision Language Models (LVLMs) have shown notable capabilities on a range of multi-modal tasks, but still face the hallucination phenomena where the ge…