arXiv Computation and Language By Sriram Selvam, Anneswa Ghosh

CITECHOICE: A Causal Audit of How Document Presentation Redistributes Citation Credit in Agentic Search

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CITECHOICE is a causal audit that examines how the presentation of documents in an agentic search engine redistributes citation credit. Using 129 everyday‑query transcripts, the study compares structured versus prose renderings of the same source while keeping all other transcript elements fixed. The results show that structured rendering increases the target’s citation count by about half a citation per answer without adding total citations or diminishing competitors’ credit, while also revealing that rank position has a larger effect on citation rates than presentation order alone.

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arXiv AI
Sep 10

AtomCite: Verification and Correction of Supplied Page-Level Citations in Multi-Page Documents

AtomCite is an agentic framework that verifies and corrects page‑level citations in multi‑page documents by parsing answers into claims, checking each claim against the cited page image, and applying a deterministic repair policy. The authors introduce DocCite, the first benchmark for this task, built on MP‑DocVQA and DUDE, containing 928 injected instances and 1,909 verified natural errors. Across Gemini, Claude, and GPT models, AtomCite achieves about 93% verification accuracy and improves citation precision from 34% to 87‑90%, while also enhancing hallucination detection in open‑source models.

By Chen Qian, Yimeng Wang, Yu Chen, Lingfei Wu, Andreas Stathopoulos