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From the 1 of 11 linked papers with an AI index.

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11 papers

cs.CL2026

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval

Qingcheng Zeng, Puxuan Yu, Aman Mehta +2

The paper defines schema retrieval—identifying the relevant tables and columns for a natural‑language question—as a distinct retrieval task and introduces a corpus‑adaptive fine‑tu…

cs.CL2026

Beyond Monolingual Deep Research: Evaluating Agents and Retrievers with Cross-Lingual BrowseComp-Plus

Yuheng Lu, Qingcheng Zeng, Heli Qi +6

Deep research agents are increasingly evaluated on their ability to search for evidence, reason over retrieved sources, and produce grounded answers. Existing browsing benchmarks,…

cs.CL2026

NOVA: NOise-aware Verbal Confidence CAlibration for Robust Large Language Models in RAG Systems

Jiayu Liu, Rui Wang, Qing Zong +9

Accurately assessing model confidence is essential for deploying large language models (LLMs) in mission-critical factual domains. While retrieval-augmented generation (RAG) is wid…

cs.AI2026

Knowledge Index of Noah's Ark

Sheng Jin, Minghao Liu, Yunze Xiao +24

Knowledge benchmarks for LLMs face three issues: scaling-driven designs that do not operationalize disciplinary representativeness; flat-payment annotation that permits lazy consen…

cs.IR2026

Dual-View Training for Instruction-Following Information Retrieval

Qingcheng Zeng, Puxuan Yu, Aman Mehta +2

Instruction-following information retrieval (IF-IR) studies retrieval systems that must not only find documents relevant to a query, but also obey explicit user constraints such as…

cs.IR2026

Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers

Qingcheng Zeng, Yuheng Lu, Zeqi Zhou +6

Code-switching is a pervasive linguistic phenomenon in global communication, yet modern information retrieval systems remain predominantly designed for, and evaluated within, monol…