A Comparative Study of Text Retrieval Models on DaReCzech
원문 초록
This article presents a comprehensive evaluation of 7 off-the-shelf document retrieval models: Splade, Plaid, Plaid-X, SimCSE, Contriever, OpenAI ADA and Gemma2 chosen to determine their performance on the Czech retrieval dataset DaReCzech. The primary objective of our experiments is to estimate the quality of modern retrieval approaches in the Czech language. Our analyses include retrieval quality, speed, and memory footprint. Secondly, we analyze whether it is better to use the model directly in Czech text, or to use machine translation into English, followed by retrieval in English. Our experiments identify the most effective option for Czech information retrieval. The findings revealed notable performance differences among the models, with Gemma22 achieving the highest precision and recall, while Contriever performing poorly. Conclusively, SPLADE and PLAID models offered a balance of efficiency and performance.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval
Dynamic Modality Interaction Modeling for Image-Text Retrieval
Bangla Parts-of-Speech Tagging using Bangla Stemmer and Rule based Analyzer
JointRank: Rank Large Set with Single Pass
From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents
Tree-Based Text Retrieval via Hierarchical Clustering in RAGFrameworks: Application on Taiwanese Regulations
토론
이 논문과 연결된 포럼 글이 아직 없습니다.