Design principles for more reliable and trustworthy AI artists
techxplore.com·53m
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Accelerating LLM inference with speculative decoding: Lessons ...
linkedin.com·1d
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Turning Incomplete Submissions into Actionable Intelligence
hackerone.com·1d
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Building Custom LLM Judges for AI Agent Accuracy
databricks.com·2d
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Here is why you have a bad experience with AI while software engineers enjoy it
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Expertise need not monopolize: Action-Specialized Mixture of Experts forVision-Language-Action Learning
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Developer Case Study: Cursor and Claude Code Suggested Building a Proxy. Shotgun CLI Found LiteLLM Instead.
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Aligning LLM agents with human learning and adjustment behavior: a dual agent approach
arxiv.org·2d
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EQ-Negotiator: Dynamic Emotional Personas Empower Small Language Models for Edge-Deployable Credit Negotiation
arxiv.org·22h
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Your First AI Application is Easier Than You Think
cloud.google.com·17h
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Databricks adds customizable evaluation tools to boost AI agent accuracy
infoworld.com·16h
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A Modular, Data-Free Pipeline for Multi-Label Intention Recognition in Transportation Agentic AI Applications
arxiv.org·22h
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🧠 Soft Architecture (Part B): Emotional Timers and the Code of Care (Part 5 of the SaijinOS series)
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Entering the Agentic Age
thedailyupside.com·12h
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