arXiv AI By Dezheng Bao, Yueci Yang, Chutian Yu, Xin Chen, Zeguo Fei, Xiang Yuan, Lijun Zhang, Jiangqian Huang, Zhengxuan Jiang, Daoze Zhang, Junru Chen, Yang Yang

PD$^3$: A Project Duplication Detection Framework via Adapted Multi-Agent Debate

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arXiv:2505. 17492v2 Announce Type: replace Abstract: Project duplication detection is critical for project quality assessment because it helps avoid investment in repeated proposals.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI
Jul 15

AAAI-26 Dual Submissions: Novel Challenges

arXiv:2607. 11918v1 Announce Type: cross Abstract: Dual submissions, in which identical or substantially similar papers are simultaneously submitted to one or more archival venues, without cross-citation or disclosure, are a growing problem for the AAAI Conference and other scientific publication venues.

By Kiri L. Wagstaff, Joydeep Biswas, Erich Merrill III, Bo An, Ida Camacho, David J. Crandall, Matthew E. Taylor
arXiv AI
6d ago

SlackBench: Benchmarking Agents on Collaborative Projects Grounded in Real Code Repositories

SlackBench is a new benchmark that evaluates AI agents on realistic collaborative research and engineering workflows, requiring joint reasoning over workplace communication and evolving repository state. The benchmark is built from privacy‑preserving reenactments of real academic projects, providing reproducible environments with multi‑party dialogue, code changes from GitHub, and Google Docs. It contains 140 queries covering heterogeneous‑source search, abstention, summarization, and inference over long conversations, and shows that current models perform well below the ceiling, indicating significant room for improvement.

By Mingxuan Li, Huanzhi Mao, Ruitao Zheng, Jarod Stanbury James, Yunze Li, Natanya Anderson, Joseph E. Gonzalez, Alex Dimakis