arXiv:2604.15488v1 Announce Type: new Abstract: Large language models (LLMs) often exhibit undesirable behaviors, such as safety violations and hallucinations. Although inference-time steering offers a cost-effective way to adjust model behavior without updating its parameters, existing methods often fail to be simultaneously effective, utility-preserving, and training-efficient due to their rigid, one-size-fits-all designs and limited adaptability. In this work, we present FineSteer, a novel steering framework that decomposes inference-time steering into two complementary stages: conditional steering and fine-grained vector synthesis, […]

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Author(s): Code Experts Originally published on Towards AI. Stop Building Chatbots. Start Building AI Agents That Actually Work. The landscape of artificial intelligence is rapidly evolving beyond simple chatbots and question-answering systems. Enter AI agents — autonomous systems that can perceive their environment, make decisions, and take actions to achieve specific goals. In this blog series, we’ll explore how to build these intelligent agents using the Agno framework. AI agents are systems that go beyond passive information retrieval. […]

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arXiv:2603.10027v1 Announce Type: new Abstract: Empiric antibiotic prescribing in high-risk clinical contexts often requires decision making under conditions of incomplete information, where inappropriate coverage or unjustified escalation may compromise safety and antimicrobial stewardship. While clinical decision-support systems have been proposed to assist in this process, many approaches lack explicit governance and evaluation mechanisms defining scope, abstention conditions, recommendation permissibility, and expected system behavior. This work specifies a governance and evaluation framework for deterministic clinical decision-support systems operating under […]

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arXiv:2604.13062v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated strong capabilities in code generation and text synthesis, yet their potential for symbolic physical reasoning in domain-specific scientific problems remains underexplored. We present a mathematical reasoning enhanced generative AI approach for optical communication formula derivation, focusing on the fiber nonlinear interference modelling. By guiding an LLM with structured prompts, we successfully reconstructed the known closed-form ISRS GN expressions and further derived a novel approximation […]

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As developers, we often need to tweak screenshots – blur out sensitive info, add annotations, or even change the text. But have you ever wanted to replace a word in a screenshot, and have it look exactly like the original? Same font, same size, same color, same style? I did, and that’s why I built Screenshot Editor – a free, open-source web app that does exactly that. In this article, I’ll walk you through the journey, the challenges, and the […]

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arXiv:2604.26956v1 Announce Type: new Abstract: The growing use of generative AI raises ethical concerns about authorship and plagiarism. This study examines how people judge the reuse of AI-generated content, focusing on moral patiency and ownership perceptions. In an experiment, participants evaluated two substantively similar manuscripts in which the original source was described as authored by a human, an AI system, or an AI agent with a human-like name. Results showed that copying AI-generated work was judged less unethical, […]

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Robust reinforcement learning methods typically focus on suppressing unreliable experiences or corrupted rewards, but they lack the ability to reason about the reliability of their own learning process. As a result, such methods often either overreact to noise by becoming overly conservative or fail catastrophically when uncertainty accumulates. In this work, we propose a meta-cognitive reinforcement learning framework that enables an agent to assess, regulate, and recover its learning behavior based on internally estimated reliability signals. The proposed […]

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Yesterday a friend and I had a conversation about category theory, how it can be a useful pattern description language, but also about how people have unrealistic expectations for it, believing category theory can deliver something for nothing. Later I ran across the following post from Qiaochu Yuan. It felt as if he had overheard my conversation and summarized it in a tweet: category theory is just some straightforwardly useful stuff for some purposes in some fields! you […]

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