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When RAG Meets Query Planning: Logical Query Trees for Resolving Exploratory Reasoning Problems
Ganlin Xu, Linghao Zhang, Zhitao Yin +7
Retrieval-Augmented Generation (RAG) effectively grounds large language models (LLMs) in external knowledge but struggles with \textbf{exploratory reasoning problems (ERPs)} that a…
What Makes an Ideal Quote? Recommending "Unexpected yet Rational" Quotations via Novelty
Bowei Zhang, Jin Xiao, Guanglei Yue +4
Quotation recommendation aims to enrich writing by suggesting quotes that complement a given context, yet existing systems mostly optimize surface-level topical relevance and ignor…
ComLQ: Benchmarking Complex Logical Queries in Information Retrieval
Ganlin Xu, Zhitao Yin, Linghao Zhang +6
Information retrieval (IR) systems play a critical role in navigating information overload across various applications. Existing IR benchmarks primarily focus on simple queries tha…
GORACS: Group-level Optimal Transport-guided Coreset Selection for LLM-based Recommender Systems
Tiehua Mei, Hengrui Chen, Peng Yu +2
Although large language models (LLMs) have shown great potential in recommender systems, the prohibitive computational costs for fine-tuning LLMs on entire datasets hinder their su…