2 papers
cs.IR2026
Clarify-Then-Search: A Clarification Benchmark for Deep Search with End-to-End Nugget Restoration
Deqiang Huang, Jingbo Zhou, Xinjiang Lu +3
Deep search is brittle on underspecified user queries: missing constraints such as time, location, scope, or definitions can lead to retrieval drift and incomplete answers. We intr…
cs.LG2026
LoReC: Rethinking Large Language Models for Graph Data Analysis
Hongyu Zhan, Qixin Wang, Yusen Tan +6
The advent of Large Language Models (LLMs) has fundamentally reshaped the way we interact with graphs, giving rise to a new paradigm called GraphLLM. As revealed in recent studies,…