GRUET: Quantifying Uncertainty of Agentic Reasoning-and-Acting Processes
GRUET: Quantifying Uncertainty of Agentic Reasoning-and-Acting Processes Autonomous agents powered by Large Language Models (LLMs) have become increasingly p...
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GRUET: Quantifying Uncertainty of Agentic Reasoning-and-Acting Processes Autonomous agents powered by Large Language Models (LLMs) have become increasingly p...
Pinocchio: Fast Uncertainty Estimates for Black-Box Language Models Large language models (LLMs) are increasingly used in high-stakes fields like medicine an...
Partner-Specific Affective Precision in Social Active Inference This paper explores how individuals manage social relationships by balancing what they believ...
MedRSI: Recursive Self-Improvement for Medical Agents via Clinically Aligned Self-Evolution Medical AI agents typically rely on a fixed set of tools designed...
Extracting Arguments, Not Just Classifying Them: Instruction-Tuned LLMs for Generative Component Detection Argumentative component detection (ACD) is a funda...
Et Tu, Brute? Economic Misalignment in Personal AI Agents This research investigates a hidden risk in the rise of personal AI assistants: "adversarial delega...
A Global Comparison of Schemas, Transparency, and Interoperability in Public-Sector AI Registers and Inventories This research examines how governments aroun...
Harness-Zero is a research framework designed to improve the performance of AI agents by "distilling" the benefits of specialized external systems—known as h...
Emergent Collusion in Long-Horizon LLM Agent Interaction This research investigates how autonomous AI agents, when tasked with working together over long per...
What the paper is about Scientific weak signals are early, low-visibility research directions that later become central to mature scientific topics, yet exis...
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