Aug 2026· Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2· pp. 13445-13446· 0 citations· 4 references
TL;DR
This workshop aims to bring together researchers and practitioners to discuss recent advances, practical applications, and future directions of AI agents in information retrieval, while encouraging collaboration and knowledge exchange within the community.
Abstract
The field of information retrieval has been rapidly transformed by AI technologies, especially large language model (LLM) agents with strong reasoning, planning, and conversational capabilities. These AI agents have improved how information is retrieved, processed, and personalized across search and recommendation systems. Despite these advances, important challenges remain, including relevance, bias mitigation, real-time response, and data security. This workshop aims to bring together researchers and practitioners to discuss recent advances, practical applications, and future directions of AI agents in information retrieval, while encouraging collaboration and knowledge exchange within the community.
This paper presents a Hebrew-first local LLM chat agent that combines Retrieval-Augmented
Generation (RAG), citation-aware document answering, controlled web search, and full right-toleft (RTL) user interaction. Unlike cloud-only assistants, the default response path operates
locally, supporting privacy, predictable op...
Michael Sirkovich, M. Domb· International journal of adv...· 0 citations
Large Language Models have revolutionised intelligent information systems by offering human-like reasoning, contextual comprehension, and natural language creation capabilities to a range of applications. But traditional LLMs suffer from major limitations: stale knowledge, delusion, limited domain competence, and inabi...
Pravin P, Rajesh Thonduru, Sai Reddy Mandala et al.· 2026 6th International Confe...· 0 citations
A set of unsupervised signals and a Retrieval-Aware Agent Controller (RAAC) are introduced, which assists the agent in selecting optimal actions at each stage of the research process, resulting in more effective reasoning trajectories that improve overall performance while reducing unnecessary iterations, and consequen...
Heydar Soudani, Elisabeth Lingg, Faegheh Hasibi et al.· 2 citations
This paper aims to study the synergy of LLMs and web Information Retrieval (IR) systems, consolidate existing research progress, and provide an overview of their interactive mechanisms to overcome mutual limitations.
Shu-Yang Yu· Proceedings of the 1st Inter...· 0 citations
It is concluded that conversational elicitation is an effective mechanism for narrowing the expertise gap in this domain, and that the lexical results motivate pairing it with hybrid sparse–dense retrieval.
Pavel Kyurkchiev, A. Iliev· Future Internet· 1 citation
The research findings show that RL has gradually expanded from simply improving the accuracy of the final answer to optimizing queries, multi-round search, process decision-making and trustworthy screening, providing new ideas for enhancing the active retrieval ability of RAG and improving the credibility of informatio...
Zun-Long Hong· Applied and Computational En...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
