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20102023
most citedPerspectives on Large Language Models for Relevance Judgment

170 citations · 387 across the 17 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.IR2022★ 14 cited

Users and Contemporary SERPs: A (Re-)Investigation Examining User Interactions and Experiences

Nirmal Roy, David Maxwell, Claudia Hauff

The Search Engine Results Page (SERP) has evolved significantly over the last two decades, moving away from the simple ten blue links paradigm to considerably more complex presenta…

cs.IR2022★ 1 cited

Moving Stuff Around: A study on efficiency of moving documents into memory for Neural IR models

Arthur Câmara, Claudia Hauff

When training neural rankers using Large Language Models, it's expected that a practitioner would make use of multiple GPUs to accelerate the training time. By using more devices,…

cs.IR2022

Sparse and Dense Approaches for the Full-rank Retrieval of Responses for Dialogues

Gustavo Penha, Claudia Hauff

Ranking responses for a given dialogue context is a popular benchmark in which the setup is to re-rank the ground-truth response over a limited set of responses, where is t…

cs.IR2022

Searching, Learning, and Subtopic Ordering: A Simulation-based Analysis

Arthur Câmara, David Maxwell, Claudia Hauff

Complex search tasks - such as those from the Search as Learning (SAL) domain - often result in users developing an information need composed of several aspects. However, current m…

cs.IR2022★ 30 cited

Diagnosing BERT with Retrieval Heuristics

Arthur Câmara, Claudia Hauff

Word embeddings, made widely popular in 2013 with the release of word2vec, have become a mainstay of NLP engineering pipelines. Recently, with the release of BERT, word embeddings…