[Submitted on 10 Nov 2025 (v1), last revised 11 Nov 2025 (this version, v2)] View a PDF of the paper titled Green AI: A systematic review and meta-analysis of its definitions, lifecycle models, hardware and measurement attempts, by Marcel Rojahn and Marcus Grum View PDF HTML (experimental) Abstract:Across the Artificial Intelligence (AI) lifecycle – from hardware to development, deployment, and …
Read More »Fashion
A Perspective from Optimal Generalization Error with Sobolev Loss
[Submitted on 31 Jan 2024 (v1), last revised 9 Nov 2025 (this version, v3)] View a PDF of the paper titled Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss, by Yahong Yang and Juncai He View PDF HTML (experimental) Abstract:Constructing the architecture of a neural network is a challenging pursuit for the machine learning community, and …
Read More »Prompting LLMs for Distribution-Faithful and Diverse Generation
[Submitted on 24 Oct 2025 (v1), last revised 7 Nov 2025 (this version, v2)] View a PDF of the paper titled String Seed of Thought: Prompting LLMs for Distribution-Faithful and Diverse Generation, by Kou Misaki and 1 other authors View PDF HTML (experimental) Abstract:We introduce String Seed of Thought (SSoT), a novel prompting method for LLMs that improves Probabilistic Instruction …
Read More »What could possibly go wrong if an enterprise replaces all its engineers with AI?
AI coding, vibe coding and agentic swarm have made a dramatic and astonishing recent market entrance, with the AI Code Tools market valued at $4.8 billion and expected to grow at a 23% annual rate. Enterprises are grappling with AI coding agents and what do about expensive human coders. They don’t lack for advice. OpenAI’s CEO estimates that AI can …
Read More »Terminal-Bench 2.0 launches alongside Harbor, a new framework for testing agents in containers
The developers of Terminal-Bench, a benchmark suite for evaluating the performance of autonomous AI agents on real-world terminal-based tasks, have released version 2.0 alongside Harbor, a new framework for testing, improving and optimizing AI agents in containerized environments. The dual release aims to address long-standing pain points in testing and optimizing AI agents, particularly those built to operate autonomously in …
Read More »Laude Institute announces first batch of ‘Slingshots’ AI grants
On Thursday, the Laude Institute announced its first batch of Slingshots grants, aimed at “advancing the science and practice of artificial intelligence.” Designed as an accelerator for researchers, the Slingshots program is meant to provide resources that would be unavailable in most academic settings, whether it’s funding, compute power, or product and engineering support. In exchange, the recipients pledge to …
Read More »[2510.26723] Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
[Submitted on 30 Oct 2025 (v1), last revised 5 Nov 2025 (this version, v2)] View a PDF of the paper titled Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning, by Masahiro Kato View PDF HTML (experimental) Abstract:The goal of policy learning is to train a policy function that recommends a treatment given …
Read More »[2509.25263] How Effective Are Time-Series Models for Precipitation Nowcasting? A Comprehensive Benchmark for GNSS-based Precipitation Nowcasting
[Submitted on 28 Sep 2025 (v1), last revised 4 Nov 2025 (this version, v3)] View a PDF of the paper titled How Effective Are Time-Series Models for Precipitation Nowcasting? A Comprehensive Benchmark for GNSS-based Precipitation Nowcasting, by Yifang Zhang and 9 other authors View PDF HTML (experimental) Abstract:Precipitation Nowcasting, which aims to predict precipitation within the next 0 to 6 …
Read More »It Doesn’t Need to Be a Chatbot
usually starts the same way. In a leadership meeting, someone says: “Let’s use AI!” Heads nod, enthusiasm builds, and before you know it, the room lands on the default conclusion: “Sure — we’ll build a chatbot.” That instinct is understandable. Large language models are powerful, ubiquitous, and fascinating. They promise intuitive access to universal knowledge and functionality. The team walks away and starts building. …
Read More »Sparsely Supervised Semantic Segmentation of Microscopy Data
[Submitted on 21 Oct 2025 (v1), last revised 30 Oct 2025 (this version, v2)] View a PDF of the paper titled {\epsilon}-Seg: Sparsely Supervised Semantic Segmentation of Microscopy Data, by Sheida Rahnamai Kordasiabi and 2 other authors View PDF HTML (experimental) Abstract:Semantic segmentation of electron microscopy (EM) images of biological samples remains a challenge in the life sciences. EM data …
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