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20192025
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cs.CL2025

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…

cs.CL2025

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…

cs.CL2022

Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples

Chengyuan Liu, Leilei Gan, Kun Kuang +1

The aim of Logic2Text is to generate controllable and faithful texts conditioned on tables and logical forms, which not only requires a deep understanding of the tables and logical…

cs.CL2021

Dialogue Inspectional Summarization with Factual Inconsistency Awareness

Leilei Gan, Yating Zhang, Kun Kuang +5

Dialogue summarization has been extensively studied and applied, where the prior works mainly focused on exploring superior model structures to align the input dialogue and the out…

cs.CL2019

Investigating Self-Attention Network for Chinese Word Segmentation

Leilei Gan, Yue Zhang

Neural network has become the dominant method for Chinese word segmentation. Most existing models cast the task as sequence labeling, using BiLSTM-CRF for representing the input an…