Tootfinder

The role of large language models in UI/UX design: A systematic literature review
Ammar Ahmed, Ali Shariq Imran
https://arxiv.org/abs/2507.04469 https://…

The role of large language models in UI/UX design: A systematic literature review
This systematic literature review examines the role of large language models (LLMs) in UI/UX design, synthesizing findings from 38 peer-reviewed studies published between 2022 and 2025. We identify key LLMs in use, including GPT-4, Gemini, and PaLM, and map their integration across the design lifecycle, from ideation to evaluation. Common practices include prompt engineering, human-in-the-loop workflows, and multimodal input. While LLMs are reshaping design processes, challenges such as halluci…

Unveiling the Landscape of Clinical Depression Assessment: From Behavioral Signatures to Psychiatric Reasoning
Zhuang Chen, Guanqun Bi, Wen Zhang, Jiawei Hu, Aoyun Wang, Xiyao Xiao, Kun Feng, Minlie Huang
https://arxiv.org/abs/2508.04531

Unveiling the Landscape of Clinical Depression Assessment: From Behavioral Signatures to Psychiatric Reasoning
Depression is a widespread mental disorder that affects millions worldwide. While automated depression assessment shows promise, most studies rely on limited or non-clinically validated data, and often prioritize complex model design over real-world effectiveness. In this paper, we aim to unveil the landscape of clinical depression assessment. We introduce C-MIND, a clinical neuropsychiatric multimodal diagnosis dataset collected over two years from real hospital visits. Each participant comple…

Hydrodynamic Effects in Cryogenic Buffer Gas Cells: Design Insights from Hybrid Simulations
Nick Vogeley, Bernd Bauerhenne, Daqing Wang
https://arxiv.org/abs/2508.04364 https://…

Hydrodynamic Effects in Cryogenic Buffer Gas Cells: Design Insights from Hybrid Simulations
Cryogenic buffer gas beam sources have become an essential tool for experiments requiring cold molecular beams with low forward velocities. Although recent experimental advances have led to significant progress in source optimization, numerical studies remain limited due to the challenges posed by the large parameter ranges required to describe both the dense buffer gas and the dilute seed molecules. In this work, we report a numerical evaluation of cryogenic buffer gas beam cells operating in …

If-T: A Benchmark for Type Narrowing
Hanwen Guo (University of Utah, USA), Ben Greenman (University of Utah, USA)
https://arxiv.org/abs/2508.03830 https://…

If-T: A Benchmark for Type Narrowing
**Context:** The design of static type systems that can validate dynamically-typed programs (**gradually**) is an ongoing challenge. A key difficulty is that dynamic code rarely follows datatype-driven design. Programs instead use runtime tests to narrow down the proper usage of incoming data. Type systems for dynamic languages thus need a **type narrowing** mechanism that refines the type environment along individual control paths based on dominating tests, a form of flow-sensitive typing. In …

Bayesian Design of Experiments in the Presence of Nuisance Parameters
Shirin Golchi, Luke Hagar
https://arxiv.org/abs/2508.03948 https://arxiv.org/pdf/2508…

Bayesian Design of Experiments in the Presence of Nuisance Parameters
Design of experiments has traditionally relied on the frequentist hypothesis testing framework where the optimal size of the experiment is specified as the minimum sample size that guarantees a required level of power. Sample size determination may be performed analytically when the test statistic has a known asymptotic sampling distribution and, therefore, the power function is available in analytic form. Bayesian methods have gained popularity in all stages of discovery, namely, design, analy…

Case Studies of Generative Machine Learning Models for Dynamical Systems
Nachiket U. Bapat, Randy C. Paffenroth, Raghvendra V. Cowlagi
https://arxiv.org/abs/2508.04459 https://

Case Studies of Generative Machine Learning Models for Dynamical Systems
Systems like aircraft and spacecraft are expensive to operate in the real world. The design, validation, and testing for such systems therefore relies on a combination of mathematical modeling, abundant numerical simulations, and a relatively small set of real-world experiments. Due to modeling errors, simplifications, and uncertainties, the data synthesized by simulation models often does not match data from the system's real-world operation. We consider the broad research question of whether …

Edit: Even More Synths! 🥳
https://matthiasott.com/notes/best-free-synthesizer-vst-plugins-in-2025

Best Free Synthesizer Plugins in 2025 · Matthias Ott
Matthias Ott is an independent user experience designer and developer from Stuttgart, Germany. Besides design practice he teaches Interface Prototyping at the Muthesius Academy of Fine Arts and Design, Kiel.

Series D, Episode 07 - Assassin
AVON: [V.O.] Scorpio, come in Scorpio.
TARRANT: Avon, what's happening?
AVON: [V.O.] Never mind what's happening. Just get me up as quickly as you can. [Cut to Domo]
NEBROX: You promised! You promised! [Back to Scorpio]
https://blake.torpidity.net/m/407/181

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

Large Language Model-based Data Science Agent: A Survey
Peiran Wang, Yaoning Yu, Ke Chen, Xianyang Zhan, Haohan Wang
https://arxiv.org/abs/2508.02744 https://

Large Language Model-based Data Science Agent: A Survey
The rapid advancement of Large Language Models (LLMs) has driven novel applications across diverse domains, with LLM-based agents emerging as a crucial area of exploration. This survey presents a comprehensive analysis of LLM-based agents designed for data science tasks, summarizing insights from recent studies. From the agent perspective, we discuss the key design principles, covering agent roles, execution, knowledge, and reflection methods. From the data science perspective, we identify key …

Ex-Ante Truthful Distribution-Reporting Mechanisms
Xiaotie Deng, Yanru Guan, Ningyuan Li, Zihe Wang, Jie Zhang
https://arxiv.org/abs/2507.04030 https://

Ex-Ante Truthful Distribution-Reporting Mechanisms
This paper studies mechanism design for revenue maximization in a distribution-reporting setting, where the auctioneer does not know the buyers' true value distributions. Instead, each buyer reports and commits to a bid distribution in the ex-ante stage, which the auctioneer uses as input to the mechanism. Buyers strategically decide the reported distributions to maximize ex-ante utility, potentially deviating from their value distributions. As shown in previous work, classical prior-dependent …