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20162024
most citedPerspectives on Large Language Models for Relevance Judgment

170 citations · 981 across the 54 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.IR2020★ 27 cited

A Benchmark for Lease Contract Review

Spyretta Leivaditi, Julien Rossi, Evangelos Kanoulas

Extracting entities and other useful information from legal contracts is an important task whose automation can help legal professionals perform contract reviews more efficiently a…

cs.IR2020★ 46 cited

Analysing the Effect of Clarifying Questions on Document Ranking in Conversational Search

Antonios Minas Krasakis, Mohammad Aliannejadi, Nikos Voskarides +1

Recent research on conversational search highlights the importance of mixed-initiative in conversations. To enable mixed-initiative, the system should be able to ask clarifying que…

cs.IR2020

An Empirical Study of Clarifying Question-Based Systems

Jie Zou, Evangelos Kanoulas, Yiqun Liu

Search and recommender systems that take the initiative to ask clarifying questions to better understand users' information needs are receiving increasing attention from the resear…

cs.IR2020★ 76 cited

Towards Question-based Recommender Systems

Jie Zou, Yifan Chen, Evangelos Kanoulas

Conversational and question-based recommender systems have gained increasing attention in recent years, with users enabled to converse with the system and better control recommenda…

cs.IR2020★ 12 cited

An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues

Svitlana Vakulenko, Evangelos Kanoulas, Maarten de Rijke

The ability to engage in mixed-initiative interaction is one of the core requirements for a conversational search system. How to achieve this is poorly understood. We propose a set…

cs.CL2020

Knowledge Graph Simple Question Answering for Unseen Domains

Georgios Sidiropoulos, Nikos Voskarides, Evangelos Kanoulas

Knowledge graph simple question answering (KGSQA), in its standard form, does not take into account that human-curated question answering training data only cover a small subset of…