arXiv:2608. 03219v1 Announce Type: new Abstract: Benchmark gains are often treated as evidence of greater LLM capability.
By Yanchao Li, Wanhao Liu, Jiaqing Xie, Ben Gao, Yanbo Wang, Tianfan Fu, Yuqiang Li
arXiv:2608. 08265v1 Announce Type: new Abstract: Oracle routing measures how much a pool of language models could gain from per-query selection, but the diagnostic has two flaws: testing against a best fixed model selected on the same examples invalidates paired inference, and a full-information oracle sees outcomes no deployable router observes.
By Ibne Farabi Shihab, Abu Sa-Adat Mohamed Moon-Im Al Ahsan, Md Najmus Swaqeeb
arXiv:2608. 09254v1 Announce Type: new Abstract: LLM analytics agents are evaluated on SQL syntax accuracy, but production failures look different: questions with two valid business definitions, questions the warehouse cannot answer, deprecated columns after a schema change, and queries that execute successfully while returning the wrong business number.
By Morris Lee
arXiv:2607. 23425v1 Announce Type: cross Abstract: Large language models increasingly write TLA$^{+}$ formal specifications from natural-language descriptions, but progress is hard to measure: existing resources grade by resemblance to a reference or by whether the output parses, neither of which shows correctness.
By Arslan Bisharat, Eric Spencer, Brian Ortiz, Khushboo Bhadauria, Mujtaba Nazari, Beatriz Santos, Anisa Ramos, TaiNing Wang, George K. Thiruvathukal, Konstantin L\"aufer, Mohammed Abuhamad
arXiv:2606. 19808v1 Announce Type: new Abstract: Test-time reasoning is increasingly used as a serving-time control knob, but extra reasoning is not uniformly valuable: it can repair failed attempts, waste compute on already-correct answers, or introduce harmful answer changes.
By Sajib Acharjee Dip, Dawei Zhou, Liqing Zhang
arXiv:2607. 17531v1 Announce Type: cross Abstract: Test-time collaboration, including self-consistency, best-of-N selection, critic models, and verifier pipelines, is often credited with broadly improving LLM reasoning, yet its gains are uneven and sometimes negative.
By Jie Hu