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20182026
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cs.IR2026

Boolean queries are all you need?

Charles L. A. Clarke, Mark D. Smucker

We equipped an LLM-based search agent with access to a Boolean retrieval engine to search the MS MARCO V2.1 deduped segment collection used by the TREC 2024 RAG track. Over a stand…

cs.IR2026

Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment

Dake Zhang, Mark D. Smucker, Charles L. A. Clarke

Many readers today struggle to assess the trustworthiness of online news because reliable reporting coexists with misinformation. The TREC 2025 DRAGUN (Detection, Retrieval, and Au…

cs.IR2025

Extending MovieLens-32M to Provide New Evaluation Objectives

Mark D. Smucker, Houmaan Chamani

Offline evaluation of recommender systems has traditionally treated the problem as a machine learning problem. In the classic case of recommending movies, where the user has provid…

cs.IR2020

Assessing top- preferences

Charles L. A. Clarke, Alexandra Vtyurina, Mark D. Smucker

Assessors make preference judgments faster and more consistently than graded judgments. Preference judgments can also recognize distinctions between items that appear equivalent un…

cs.IR2018

Evaluating Sentence-Level Relevance Feedback for High-Recall Information Retrieval

Haotian Zhang, Gordon V. Cormack, Maura R. Grossman +1

This study uses a novel simulation framework to evaluate whether the time and effort necessary to achieve high recall using active learning is reduced by presenting the reviewer wi…