Tootfinder

Intention-Driven Generation of Project-Specific Test Cases
Binhang Qi, Yun Lin, Xinyi Weng, Yuhuan Huang, Chenyan Liu, Hailong Sun, Jin Song Dong
https://arxiv.org/abs/2507.20619

Intention-Driven Generation of Project-Specific Test Cases
Test cases are valuable assets for maintaining software quality. While numerous automated techniques have been proposed for generating tests (either by maximizing code coverage or by translating focal code into test code), practical tests are seldom driven by coverage alone. In real projects, each test reflects a developer's validation intention for a specific behaviour and embodies rich, project-specific knowledge: which specific APIs to call and what assertions truly matter. Without consideri…

AHAMask: Reliable Task Specification for Large Audio Language Models without Instructions
Yiwei Guo, Bohan Li, Hankun Wang, Zhihan Li, Shuai Wang, Xie Chen, Kai Yu
https://arxiv.org/abs/2509.01787

AHAMask: Reliable Task Specification for Large Audio Language Models without Instructions
Although current large audio language models (LALMs) extend text large language models (LLMs) with generic acoustic understanding abilities, they usually suffer from instruction sensitivity, where different instructions of the same intention can yield drastically different outcomes. In this work, we propose AHAMask, where we simply mask some of the attention heads in the decoder-only LLM backbone of LALMs, to trigger specific acoustic task functionalities without instructions. These masks are e…

Quotas for scholarship recipients: an efficient race-neutral alternative to affirmative action?
Louis Gleyo
https://arxiv.org/abs/2507.17191 https://arxiv.…

Quotas for scholarship recipients: an efficient race-neutral alternative to affirmative action?
Since 2018, France's centralized higher education platform, Parcoursup, has implemented quotas for scholarship recipients, with program-specific thresholds based on the applicant's composition. Using difference-in-differences methods, I find these quotas enabled scholarship students to access more selective programs, though intention-to-treat effects remain modest (maximum 0.10 SD). Matching methods reveal that the policy improved the scholarship students' waiting list positions relative to tho…