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20212026
most citedEvaluating Generative Ad Hoc Information Retrieval

44 citations · 167 across the 30 of their papers we have counts for

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9 papers · 1 filter

cs.IR2026

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…

cs.IR2026

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…

cs.IR2026

Reproducing LightMem: When Does Memory Construction Help Over Raw-Turn Retrieval?

Yongjie Zhou, Shuai Wang, Bevan Koopman +1

Long-term conversational agents require access to information from earlier interactions, such as a user's preferences, past requests, or previously mentioned facts. Repeatedly prov…

cs.AI2026

NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMs

Shuaidi Wang, Zhan Zhuang, Ruping Huang +1

Diffusion Large Language Models (dLLMs) have emerged as a promising non-autoregressive generative paradigm. Given the prohibitive computational cost of full fine-tuning, Parameter-…

cs.CR2026

Can It Reach the Generator? Investigating the Survival of Prompt-Injection Attacks in Realistic RAG Settings

Yu Yin, Shuai Wang, Bevan Koopman +1

Recent generative engine optimisation (GEO) research has shown that prompt-injection attacks can push a target product to the top of an LLM's recommendation list, with the stronges…

cs.IR2026

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,…

cs.IR2026

Beyond Chunk-Then-Embed: A Comprehensive Taxonomy and Evaluation of Document Chunking Strategies for Information Retrieval

Yongjie Zhou, Shuai Wang, Bevan Koopman +1

Document chunking is a critical preprocessing step in dense retrieval systems, yet the design space of chunking strategies remains poorly understood. Recent research has proposed s…

cs.CR2026

The Vulnerability of LLM Rankers to Prompt Injection Attacks

Yu Yin, Shuai Wang, Bevan Koopman +1

Large Language Models (LLMs) have emerged as powerful re-rankers. Recent research has however showed that simple prompt injections embedded within a candidate document (i.e., jailb…

cs.IR2026

AutoBool: An Reinforcement-Learning trained LLM for Effective Automated Boolean Query Generation for Systematic Reviews

Shuai Wang, Harrisen Scells, Bevan Koopman +1

We present AutoBool, a reinforcement learning (RL) framework that trains large language models (LLMs) to generate effective Boolean queries for medical systematic reviews. Boolean…