22 papers · ranked by Valyu relevance
Tom Pollard, Thomas Sounack, Catherine A. Gao, Leo Anthony Celi + 5 more
Introduction The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement was published to improve the reporting and critical appraisal of prediction model studies for diagnosis and prognosis. This paper describes the processes and methods that will be used to…
Rui Xu, Jiawei Chen, Zhaoxia Yin, Cong Kong + 2 more
The widespread use of large language models (LLMs) and open-source code has raised ethical and security concerns regarding the distribution and attribution of source code, including unauthorized redistribution, license violations, and misuse of code for malicious purposes. Watermarking has emerged as a promising…
Rachel Kowert
So called “toxic behaviors” (e.g., hate speech, harassment, doxxing) are pervasive in online gaming communities, with research consistently documenting significant negative consequences for player wellbeing, community health, and industry revenue. While gaming studios and platforms have developed a range of reactive…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Adam B. Pollack, Lisa Auermuller, Casey D. Burleyson, Jentry Campbell + 20 more
People around the world seek climate risk information to guide their decisions. For instance, projections about future flood risk inform where households choose to live, how lenders manage credit risks, and which communities receive federal funding. Yet data limitations and fundamental validation challenges raise…
Saul Martin-Rodriguez, Rodrigo Fernandez-Gonzalo, David Moher
Title: Summary points 1. Systematic reviews and meta-analyses underpin clinical guidelines and health policy, yet their validity may be compromised by limited access to underlying datasets and associated analytical code. 2. Reliance on incomplete or inconsistently reported summary statistics forces researchers to use…
Huixin Zhan, Jason H. Moore
AI disclosure mandates have rapidly become standard in scientific publishing, a genuine success of scholarly self-governance. Yet across 10,000 bioRxiv preprints, disclosure tracks only modestly with code and data sharing. The next phase of policy should pair “whether” with “how,” alongside independent transparency…
Alexander Wan, Kevin Klyman, Sayash Kapoor, Nestor Maslej + 4 more
Foundation model developers are among the world's most important companies. As these companies become increasingly consequential, how do their transparency practices evolve? The 2025 Foundation Model Transparency Index is the third edition of an annual effort to characterize and quantify the transparency of foundation…
Anita Bandrowski, Amit Namburi, Adam Ferguson, Candace L. Floyd + 1 more
Preclinical research in traumatic brain injury (TBI) continues to significantly increase knowledge and yield a large number of peer-reviewed studies, but translation of these results to the clinical setting has been minimal. Rigor and transparency factors such as concealment of group allocation (e.g., “blinding’’) or…
Georgios Angelopoulos, Dimitri Lacroix, Ricarda Wullenkord, Alessandra Rossi + 2 more
As robots become increasingly integrated into our daily lives, the need to make them transparent has never been more critical. Yet, despite its importance in human-robot interaction, a standardized measure of robot transparency has been missing until now. This paper addresses this gap by presenting the first…
Yuqing Nie, Chong Wang, Guosheng Xu, Guoai Xu + 3 more
Code Large Language Models (Code LLMs) have revolutionized software development but raised critical concerns regarding code provenance, copyright protection, and security. Existing code watermarking approaches suffer from two fundamental limitations: black-box methods either exhibit detectable syntactic patterns…
Chen Yang, Xianyang Zhang, Jun Chen
Spatial transcriptomics analyses often require coordinating specialized Python and R methods. When analytical intent is translated through ad hoc scripts or unconstrained LLM generated code, workflows can be difficult to inspect, rerun, or compare. We present ChatSpatial, a schema enforced orchestration framework in…
Authors not listed
Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Anna Spagnolli, Cecilia Tolomini, Elisa Beretta, Patrik Pluchino + 2 more
Algorithmic systems play an essential role in healthcare and are pervasively incorporated into medical software and equipment. In the European Union, providers must share transparency information with deployers (users) via a document called Instructions for Use (IFU, Directive 2024/1689 or AI Act). This study tests the…
Yuchen Chen, Yuan Xiao, Chunrong Fang, Zhenyu Chen + 1 more
The proliferation of large language models for code (CodeLMs) and open-source contributions has heightened concerns over unauthorized use of source code datasets. While watermarking provides a viable protection mechanism by embedding ownership signals, existing methods rely on detectable trigger-target patterns and are…
Authors not listed
Chemistry curricula often separate “wet” experimental work from “dry” computation, yet modern discovery increasingly demands both. This Perspective offers an instructor-ready roadmap to train “hybrid chemists” within existing courses. We distill recent advances in machine learning, automation, and real-time analytics…
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…
Soohyeon Choi, Debin Gao, Yue Duan
Attributing code to the large language model that produced it is essential for provenance, licensing, and misuse accountability, yet no deployed watermark meets this need. Generation-time schemes require access to the producing model and cannot be applied to third-party code, while post-hoc schemes work on any code but…
Hung Q. Vo, Huy Q. Vo, Son T. Ly, Zhihao Wan + 5 more
Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feature extraction, and spatial organization analysis. However, these tools often require manual intervention and are not well integrated with code-driven automation…
Jordan J. Smith, Xi Wang, Matthew McPheeters, Made Airanthi Widjaja-Adhi + 4 more
Spatial transcriptomics enables high-resolution mapping of gene expression in intact tissues but remains challenging due to complex computational workflows that limit accessibility and reproducibility. Here, we present a Model Context Protocol (MCP) framework enabling natural language-driven spatial transcriptomics…