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Guido Zuccon

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Preprint Oct 2026

The Impact of Backbone Evolution on LLM-Based Relevance Assessments

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 with human judgements under the same prompt. We challenge this understanding by investigating the behavior of LLM-based relevance judges under...

Chu-Chun Yu, Guido Zuccon, T. Leelanupab · 0 citations
Preprint Aug 2026

ITER: Interaction-Aware Retrieval for Agentic Search

ITER, an agent interaction-aware dense retriever trained using agent trajectory learning signals, is introduced andlations show that structured interaction history and pre-search reasoning provide complementary retrieval context, while previously visited and useful documents provide the strongest trajectory-relative su...

Hao-Dong Chen, Shuai Wang, Yu Yin et al. · 0 citations

Search, Inspect, Fetch: Exploiting Boolean Retrieval for Deep-Research Agents

This work introduces S IEVE, a search–inspect–fetch strategy built around a Boolean Query Language (BQL), which improves accuracy with every tested ranker, and the accuracy–context advantage persists across retriever choices and agent backbones.

Shuai Wang, Hao-Dong Chen, Yu Yin et al. · 0 citations
Preprint Aug 2026

How retriever redundancy and diversity impact RAG effectiveness

It is shown that duplicate redundancy and LLM paraphrasing does not significantly improve answer correctness, however, providing diverse documents is highly beneficial, improving answer correctness by 17%-47%.

Jonathan J. Ross, B. Koopman, A. H. van der Vegt et al. · 2 citations
Preprint Aug 2026

ITER: Interaction-Aware Retrieval for Agentic Search

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 needed at each stage. However, existing retriever training typically relies only on the sub-query and its corresponding search results at the cur...

Hao-Dong Chen, Shuai Wang, Yu Yin et al. · 0 citations
#artificial intelligence Preprint Aug 2026

Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Search Agents

This work introduces Sieve, a search-inspect-fetch strategy driven by a Boolean Query Language (BQL): it searches webpage fields to filter candidates, uses an interchangeable ranker to order them, presents structure-rich result cards for inspection, and fetches only selected sections.

Shuai Wang, Hao-Dong Chen, Yu Yin et al. · 4 citations

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