The expansion of exoplanet observations has created a need for flexible, accessible, and user-friendly workflows. Transmission spectroscopy has become a key technique for probing atmospheric composition of transiting exoplanets. The analyses of these data require the combination of archival queries, literature search, the use of radiative transfer models, and Bayesian retrieval frameworks, each demanding specialized expertise. Modern large language models enable the coordinated execution of complex, multi-step tasks by AI agents with tool integration, structured prompts, and iterative reasoning. In this study we present ASTER, an Agentic Science Toolkit for Exoplanet Research. ASTER is an orchestration framework that brings LLM capability to the exoplanetary community by enabling LLM-driven interaction with integrated domain-specific tools, workflow planning and management, and support for common data analysis tasks. Currently ASTER incorporates tools for downloading planetary parameters and observational datasets from the NASA Exoplanet Archive, as well as the generation of transit spectra from the TauREx radiative transfer model, and the completion of Bayesian retrieval of planetary parameters with TauREx. Beyond tool integration, the agent assists users by proposing alternative modeling approaches, reporting potential issues and suggesting solutions, and interpretations. We demonstrate ASTER's workflow through a complete case study of WASP-39b, performing multiple retrievals using observational data available on the archive. The agent efficiently transitions between datasets, generates appropriate forward model spectra and performs retrievals. ASTER provides a unified platform for the characterization of exoplanet atmospheres. Ongoing development and community contributions will continue expanding ASTER's capabilities toward broader applications in exoplanet research.
Inria（法国国家信息与自动化研究所）；CNRS（法国国家科学研究中心）；RENATER（法国国家电信研究网络）；University de Lorraine（洛林大学）
This paper describes Asteroid, the PyTorch-based audio source separation toolkit for researchers. Inspired by the most successful neural source separation systems, it provides all neural building blocks required to build such a system. To improve reproducibility, Kaldi-style recipes on common audio source separation datasets are also provided. This paper describes the software architecture of Asteroid and its most important features. By showing experimental results obtained with Asteroid's recipes, we show that our implementations are at least on par with most results reported in reference pap…
A Dual-Helix Governance Approach Towards Reliable Agentic Artificial Intelligence for WebGIS Development
Geographic Information Systems Center, Florida International University（佛罗里达国际大学地理信息系统中心）；Geospatial Analytics, Technology and Open Research Lab, University of Florida（佛罗里达大学地理空间分析、技术与开放研究实验室）
Can Agentic Trading Systems Pay for Their Own Intelligence?
HKUST(GZ)（香港科技大学（广州））；Paradoox AI（悖论人工智能公司）；E Fund Management Co., Ltd（易方达基金管理有限公司）；MBZUAI（Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学））；The University of Tokyo（东京大学）
CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding
New York University Abu Dhabi（纽约大学阿布扎克校区）；Nanyang Technological University（南洋理工大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Harvard University（哈佛大学）；Zhejiang University（浙江大学）；University of Electronic Science and Technology of China（电子科技大学）；Beijing University of Technology（北京理工大学）；The Hong Kong Polytechnic University（香港理工大学）
SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs
University of California San Diego（加州大学圣地亚哥分校）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Peking University（北京大学）；University of California, Los Angeles（加州大学洛杉矶分校）；California Institute of Technology（加州理工学院）；ETH Zurich（苏黎世联邦理工学院）
KISS - Knowledge Infrastructure for Scientific Simulation: A Scaffolding for Agentic Earth Science
State Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing（水利灾害预防国家重点实验室，河海大学，南京）；Yangtze Institute for Conservation and Development, Hohai University, Nanjing（长江保护与发展研究院，河海大学，南京）；Department of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada（生物资源工程系，麦吉尔大学，圣安妮-德-贝尔贝夫，魁北克，加拿大）；Ottawa Research and Development Centre, Agriculture & Agri-Food Canada, Ottawa, Ontario, K1A 0C6, Canada（渥太华研发中心，加拿大农业与食品部，渥太华，安大略，K1A 0C6，加拿大）；College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing（水利水电工程学院，河海大学，南京）；Meta Platforms Inc.（Meta平台公司）；Nanjing Hydraulic Research Institute, Nanjing（南京水利研究院）
What If Prompt Injection Never Left? Rethinking Agent Security through Cross-Session Stored Prompt Injection
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）；AI Sec Lab, Beijing Chaitin Technology Co.,Ltd（北京柴坦科技有限公司AI安全实验室）
