Zobrazeno 1 - 10
of 461
pro vyhledávání: '"YU, WEIJIE"'
Autor:
Sun, Zhongxiang, Zang, Xiaoxue, Zheng, Kai, Song, Yang, Xu, Jun, Zhang, Xiao, Yu, Weijie, Li, Han
Retrieval-Augmented Generation (RAG) models are designed to incorporate external knowledge, reducing hallucinations caused by insufficient parametric (internal) knowledge. However, even with accurate and relevant retrieved content, RAG models can sti
Externí odkaz:
http://arxiv.org/abs/2410.11414
Commercial recommender systems face the challenge that task requirements from platforms or users often change dynamically (e.g., varying preferences for accuracy or diversity). Ideally, the model should be re-trained after resetting a new objective f
Externí odkaz:
http://arxiv.org/abs/2410.10639
Autor:
Qin, Weicong, Xu, Yi, Yu, Weijie, Shen, Chenglei, Zhang, Xiao, He, Ming, Fan, Jianping, Xu, Jun
Sequence recommendation (SeqRec) aims to predict the next item a user will interact with by understanding user intentions and leveraging collaborative filtering information. Large language models (LLMs) have shown great promise in recommendation task
Externí odkaz:
http://arxiv.org/abs/2409.06377
In this paper, we address the issue of using logic rules to explain the results from legal case retrieval. The task is critical to legal case retrieval because the users (e.g., lawyers or judges) are highly specialized and require the system to provi
Externí odkaz:
http://arxiv.org/abs/2403.01457
Reinforcement learning (RL) has gained traction for enhancing user long-term experiences in recommender systems by effectively exploring users' interests. However, modern recommender systems exhibit distinct user behavioral patterns among tens of mil
Externí odkaz:
http://arxiv.org/abs/2401.09034
Legal document retrieval and judgment prediction are crucial tasks in intelligent legal systems. In practice, determining whether two documents share the same judgments is essential for establishing their relevance in legal retrieval. However, existi
Externí odkaz:
http://arxiv.org/abs/2312.09591
Autor:
Dai, Sunhao, Shao, Ninglu, Zhao, Haiyuan, Yu, Weijie, Si, Zihua, Xu, Chen, Sun, Zhongxiang, Zhang, Xiao, Xu, Jun
The debut of ChatGPT has recently attracted the attention of the natural language processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT shows significant improvement in a range of downstream NLP tasks, but the capabil
Externí odkaz:
http://arxiv.org/abs/2305.02182
As an essential operation of legal retrieval, legal case matching plays a central role in intelligent legal systems. This task has a high demand on the explainability of matching results because of its critical impacts on downstream applications -- t
Externí odkaz:
http://arxiv.org/abs/2207.04182
Publikováno v:
In Transport Policy December 2024 159:375-391
Publikováno v:
In Thin-Walled Structures December 2024 205 Part B