Large language models (LLMs) are increasingly used to produce the relevance labels that underpin the evaluation of information retrieval (IR) and retrieval-augmented generation systems. Yet delegating relevance assessment to an LLM raises a meta-evaluation question that is hard to answer with existing resources: when,...
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi et al.· Proceedings of the 35th ACM...· 0 citations
Agents in knowledge-intensive domains require not only knowledge retrieval, but also the skills to effectively use retrieved knowledge. Since domain knowledge is often highly complex, agents must possess strong reasoning capabilities in order to perform tasks effectively. In the legal domain, different legal systems ex...
Yi-Ran Hu, Rong-Xin Cheng, Hai-Tao Li et al.· Proceedings of the 35th ACM...· 0 citations
seek, Self-Evaluative Exploration for Knowledge Retrieval, a training-free framework that addresses this limitation through iterative corpus interaction at test time through iterative corpus interaction at test time.
Amin Bigdeli, Radin Hamidi Rad, Negar Arabzadeh et al.· Proceedings of the 35th ACM...· 0 citations
Question's Gambit is introduced, a first-move retrieval module that decomposes the question into a set of clues, reformulates them into complementary searches, consolidates the retrieved results, and reranks the candidate pool before the agent begins its iterative search-and-reasoning process.
