arXiv:2604.13120v1 Announce Type: new Abstract: Large language models generate plausible code but cannot verify correctness. Existing multi-agent systems simulate execution or leave verification optional. We introduce execution-grounded verification as a first-class principle: every code change must survive sandboxed execution before propagation. We instantiate this principle in AGENTFORGE, a multi-agent framework where Planner, Coder, Tester, Debugger, and Critic agents coordinate through shared memory and a mandatory Docker sandbox. We formalize software engineering with LLMs as an iterative decision process […]

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arXiv:2603.20309v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit hallucinations in knowledge-intensive tasks. Graph-based retrieval augmented generation (RAG) has emerged as a promising solution, yet existing approaches suffer from fundamental recall and precision limitations when operating over black-box knowledge graphs — graphs whose schema and structure are unknown in advance. We identify three core challenges that cause recall loss (semantic instantiation uncertainty and structural path uncertainty) and precision loss (evidential comparison uncertainty). To address these challenges, we […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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arXiv:2602.09064v1 Announce Type: new Abstract: Open Source Software (OSS) projects follow diverse lifecycle trajectories shaped by evolving patterns of contribution, coordination, and community engagement. Understanding these trajectories is essential for stakeholders seeking to assess project organization and health at scale. However, prior work has largely relied on static or aggregated metrics, such as project age or cumulative activity, providing limited insight into how OSS sustainability unfolds over time. In this paper, we propose a hierarchical predictive framework that […]

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Last week, a post about my open-source project CocoIndex Code hit 54K+ views on X after @RoundtableSpace shared it. The tweet was simple: “CocoIndex Code gives your coding agent a brain.” That one line captured exactly what we built and why it matters. The problem is straightforward. Every time your AI coding agent needs context about your codebase, it pulls in entire files. Function signatures, import statements, docstrings, blank lines, comments you wrote at 2am — everything gets […]

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One of the most popular AI assistants of the developer community is undergoing a major shift in terms of pricing. GitHub Copilot will now transition from subscription based billing to usage based billing. A single credit would cost $0.01 USD, and the amount would rake up based on the said task. For paid users, code autocomplete stays unlimited. But features like Copilot Chat, CLI actions, or cloud agents are now tied to monthly credit limits. Plans will still […]

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arXiv:2604.08549v1 Announce Type: new Abstract: We introduce VerifAI, an open-source expert system for biomedical question answering that integrates retrieval-augmented generation (RAG) with a novel post-hoc claim verification mechanism. Unlike standard RAG systems, VerifAI ensures factual consistency by decomposing generated answers into atomic claims and validating them against retrieved evidence using a fine-tuned natural language inference (NLI) engine. The system comprises three modular components: (1) a hybrid Information Retrieval (IR) module optimized for biomedical queries (MAP@10 of 42.7%), (2) […]

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arXiv:2601.15408v1 Announce Type: new Abstract: Medical vision-language models can automate the generation of radiology reports but struggle with accurate visual grounding and factual consistency. Existing models often misalign textual findings with visual evidence, leading to unreliable or weakly grounded predictions. We present CURE, an error-aware curriculum learning framework that improves grounding and report quality without any additional data. CURE fine-tunes a multimodal instructional model on phrase grounding, grounded report generation, and anatomy-grounded report generation using public datasets. The […]

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Hey everyone, I recently built my first reinforcement learning agent to play Super Mario Bros and Super Mario World. I documented the whole process in a video, and would love any feedback from people who know RL. I’m still learning and I’m sure there are better approaches I missed. Happy to answer any questions about the process too. https://youtu.be/6FQKz-yAt5Y submitted by /u/Marcell0123 [link] [comments]

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If you’ve worked with Ethereum and then tried Solana, you probably felt confused by how different everything looks. The account model especially feels strange. But here’s the thing: it’s not just different for the sake of being different. Ethereum and Solana made completely opposite choices about how to organize data, and these choices matter a lot. Let’s break down what makes Solana’s account model unique and why it works the way it does. The Big Picture: Two Different […]

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