5 citations · 8 across the 10 of their papers we have counts for
11 papers
The Impact of Backbone Evolution on LLM-Based Relevance Assessments
Chuting Yu, Guido Zuccon, Teerapong Leelanupab
LLMs are evolving rapidly, with newer models offering stronger capabilities. This suggests that in LLM-based relevance judging, more capable models will achieve higher agreement wi…
ITER: Interaction-Aware Retrieval for Agentic Search
Haodong Chen, Shuai Wang, Yu Yin +3
Deep-research agents answer complex user questions through an iterative sequence of search steps, where the agent autonomously formulates sub-queries to retrieve the evidence neede…
Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Search Agents
Shuai Wang, Haodong Chen, Yu Yin +3
Existing deep-search agents use a Search-Visit workflow that retrieves whole webpages without considering the structure they expose through titles, headings, sections, and metadata…
How retriever redundancy and diversity impact RAG effectiveness
Jonathan J Ross, Bevan Koopman, Anton van der Vegt +1
In RAG, while the retriever typically ranks documents by their individual relevance to the query, the generator instead produces an answer based on the retrieved documents as a who…
More Efficient LLM Reranking with Whole-Pool, Setwise, Long-Context Language Models
Hang Li, Chuting Yu, Teerapong Leelanupab +2
LLM-based re-rankers produce rankings through repeated local comparisons (listwise, pairwise or pointwise), requiring many sequential model calls. We study how long-context LLMs ca…
On the impact of retrieved content representations in RAG Pipelines
Jonathan J Ross, Bevan Koopman, Anton van der Vegt +1
Retrieval-Augmented Generation (RAG) supplements a language model's input with retrieved documents, yet most RAG pipelines inherit retrieval components designed for human readers.…
DiffRetriever: Parallel Representative Tokens for Retrieval with Diffusion Language Models
Shuai Wang, Yu Yin, Shengyao Zhuang +2
This paper shows how diffusion language models (DLMs) can be used as effective and efficient retrievers. Existing DLM-based retrievers (e.g., DiffEmbed) follow BERT-style encoding,…
Where Relevance Emerges: A Layer-Wise Study of Internal Attention for Zero-Shot Re-Ranking
Haodong Chen, Shengyao Zhuang, Zheng Yao +2
Zero-shot document re-ranking with Large Language Models (LLMs) has evolved from Pointwise methods to Listwise and Setwise approaches that optimize computational efficiency. Despit…
When LLM Judges Inflate Scores: Exploring Overrating in Relevance Assessment
Chuting Yu, Hang Li, Guido Zuccon +2
Human relevance assessment is time-consuming and cognitively intensive, limiting the scalability of Information Retrieval evaluation. This has led to growing interest in using larg…
Beyond GeneGPT: A Multi-Agent Architecture with Open-Source LLMs for Enhanced Genomic Question Answering
Haodong Chen, Guido Zuccon, Teerapong Leelanupab
Genomic question answering often requires complex reasoning and integration across diverse biomedical sources. GeneGPT addressed this challenge by combining domain-specific APIs wi…
Enriching Existing Test Collections with OXPath
Philipp Schaer, Mandy Neumann
Extending TREC-style test collections by incorporating external resources is a time consuming and challenging task. Making use of freely available web data requires technical skill…