1 citations · 1 across the 5 of their papers we have counts for
5 papers
LeTS: Learning to Think-and-Search via Process-and-Outcome Reward Hybridization
Qi Zhang, Shouqing Yang, Lirong Gao +8
Large language models (LLMs) have demonstrated impressive capabilities in reasoning with the emergence of reasoning models like OpenAI-o1 and DeepSeek-R1. Recent research focuses o…
QUILL: Quotation Generation Enhancement of Large Language Models
Jin Xiao, Bowei Zhang, Qianyu He +6
While Large language models (LLMs) have become excellent writing assistants, they still struggle with quotation generation. This is because they either hallucinate when providing f…
SEGMENT+: Long Text Processing with Short-Context Language Models
Wei Shi, Shuang Li, Kerun Yu +9
There is a growing interest in expanding the input capacity of language models (LMs) across various domains. However, simply increasing the context window does not guarantee robust…
Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals
Lida Chen, Zujie Liang, Xintao Wang +7
Large language models (LLMs) have achieved great success, but their occasional content fabrication, or hallucination, limits their practical application. Hallucination arises becau…
CubeFlow: Money Laundering Detection with Coupled Tensors
Xiaobing Sun, Jiabao Zhang, Qiming Zhao +5
Money laundering (ML) is the behavior to conceal the source of money achieved by illegitimate activities, and always be a fast process involving frequent and chained transactions.…