6 citations · 17 across the 9 of their papers we have counts for
9 papers
Mitigating Entity-Level Hallucination in Large Language Models
Weihang Su, Yichen Tang, Qingyao Ai +3
The emergence of Large Language Models (LLMs) has revolutionized how users access information, shifting from traditional search engines to direct question-and-answer interactions w…
STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionals
Weihang Su, Yiran Hu, Anzhe Xie +6
Statute retrieval aims to find relevant statutory articles for specific queries. This process is the basis of a wide range of legal applications such as legal advice, automated jud…
Caseformer: Pre-training for Legal Case Retrieval Based on Inter-Case Distinctions
Weihang Su, Qingyao Ai, Yueyue Wu +5
Legal case retrieval aims to help legal workers find relevant cases related to their cases at hand, which is important for the guarantee of fairness and justice in legal judgments.…
Wikiformer: Pre-training with Structured Information of Wikipedia for Ad-hoc Retrieval
Weihang Su, Qingyao Ai, Xiangsheng Li +4
With the development of deep learning and natural language processing techniques, pre-trained language models have been widely used to solve information retrieval (IR) problems. Be…
THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case Entailment
Haitao Li, Changyue Wang, Weihang Su +3
This paper describes the approach of the THUIR team at the COLIEE 2023 Legal Case Entailment task. This task requires the participant to identify a specific paragraph from a given…
THUIR@COLIEE 2023: Incorporating Structural Knowledge into Pre-trained Language Models for Legal Case Retrieval
Haitao Li, Weihang Su, Changyue Wang +3
Legal case retrieval techniques play an essential role in modern intelligent legal systems. As an annually well-known international competition, COLIEE is aiming to achieve the sta…