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Trevor Adriaanse

SIGIR 2026×3检索与知识数据与预训练强化学习与后训练可解释性效率与系统
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0 一作 · 3 篇 · SIGIR 2026

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2026 顶会论文

3
作者位次 #3/5SIGIR 2026Oral· Information Retrieval (Full)

Search for Coverage: Learning Coverage-Aware Retrieval with Augmented Sub-Question Answerability

Jia-Huei Ju · Eugene Yang · Trevor Adriaanse · Suzan Verberne · Andrew Yates

摘要

Long-form Retrieval-Augmented Generation (RAG) brings the challenge of coverage-based ranking, because ranking methods must ensure the inclusion of comprehensive relevant nuggets (i.e., facts), which can thereby be synthesized into a comprehensive output. In this work, we propose CoveR, a dense r...

检索与知识强化学习与后训练数据与预训练OpenReview
作者位次 #4/5SIGIR 2026Poster· Information Retrieval (Short)

Clustering-Based Methods for Vector-Based Pseudo-Relevance Feedback

Xavier Velez · Andrew Yates · Eugene Yang · Trevor Adriaanse · Sanjeev Khudanpur

摘要

Prior work has shown that vector-based pseudo relevance feedback (PRF) is an effective technique for query expansion for improving retrieval results in dense information retrieval. In dense retrieval, ColBERT-PRF has emerged as a novel mechanism, using cluster centroids built from feedback docume...

检索与知识可解释性效率与系统OpenReview
作者位次 #5/7SIGIR 2026Poster· Information Retrieval (Resource)

CoverageBench: Evaluating Information Coverage across Tasks and Domains

Saron Samuel · Andrew Yates · Dawn Lawrie · Ian Soboroff · Trevor Adriaanse · Benjamin Van Durme · Eugene Yang

摘要

We wish to measure the information coverage of an ad hoc retrieval algorithm, that is, how much of the range of available relevant information is covered by the search results.Information coverage is a central aspect for retrieval, especially when the retrieval system is integrated with generativ...

评测与基准检索与知识数据与预训练OpenReview

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