Work

Don’t Be Misled by Style: A Style-Adaptive Reranker for Capturing Effective Knowledge in Retrieval-Augmented Generation

Year: 2026

Type: conference-paper

Abstract: Ruwen Zhang, Bo Liu, Zhang Sheng Xiang, Yida Chen, Hantao Zhao, Ding Ding, Jiahui Jin, Jiuxin Cao. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.18653/v1/2026.acl-long.302

Authors: Ruwen Zhang, Bo Liu, Zhang Sheng Xiang, Yida Chen, Hantao Zhao, Ding Ding, Jiahui Jin, Jiuxin Cao

Institutions: Southeast University, Purple Mountain Laboratories

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Natural Science Foundation of China, Ministry of Education of the People's Republic of China, Government of Jiangsu Province, Ministry of Education, India, Natural Science Foundation of Jiangsu Province, Key Laboratory of Computer Network and Information Integration

Awards: G1019060874, G164085555, G2635751390, G3119304389, G36496830, G4292527145, G4319099995, G5554206936, G5623484275, G5988281228, G6153596011, G6500690629, G7379951849, G7382607216, G8361240271, G8735051588, G8898464643

OpenAlex ID: W7166799348

FWCI: 8.935

Cites:

Cited by: 1

Related to: 10