AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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9,568 papers
Together, the survival and rationale analyses reveal distinct temporal reliability regimes and model-specific"failure fingerprints", offering an evaluation lens for diagnosing inconsistency in multi-turn agent behavior.
RLCDAlignBench is presented, which benchmarks Jev on ten alignment failures: sycophancy, jailbreaks, deception, prompt injection, hallucination, privacy violation, social bias, reward hacking, concealing uncertainty, and power seeking.
CAR-bench evaluates whether tool-using agents stay reliable under real-world uncertainty, executing every tool inside the evaluator so that each tool-result exchange is a separate agent round-trip. A conventional next-action agent can batch parallel tool calls, but a chain of dependent calls costs it one model call per...
Domain-specific RAG improved evidence grounding and response quality for cancer registry questions while enabling citation-supported assistance across complexity levels, and demonstrates the potential of human-centered, citation-grounded AI to support cancer registrars while preserving human oversight for final coding...
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This work introduces MeshHeal, a fully decentralized self-healing framework that couples ability-matched peer review across two timescales and introduces Model-Backed MAS Evaluation, which ties ability assignments to execution models, since prompt-based ability assignments alone can leave routing errors hidden.
A behavioral stress test showing that more reasoning is not always better; forecasting agents should first estimate which evidence source deserves control, routing policies should themselves adapt under auditable constraints, and reproducibility artifacts are available at https://github.com/louiswang524/forcastagent.
WARP is introduced, a family of post-retrieval algorithms that calibrate retrieved evidence to the population's opinion distribution, and its domain-matched variants reduce distributional error by at least 43% with sub-second latency.
The limits of algorithmic safety verification for Turing-complete self-modifying systems, the class in which recursive self-improvement takes place, are established, both for a fixed system and across its own modification.
MobileGym enables two capabilities previously out of reach for everyday apps: verifiable outcome signals through deterministic state-based judging over structured JSON state, and scalable online RL through low-cost parallel rollouts through low-cost parallel rollouts.
This work proposes DreamAvoid, a critical-phase test-time dreaming framework that enables VLA models to anticipate and avoid failures, and introduces an autonomous boundary learning paradigm to refine the system's understanding of the subtle boundary between success and failure.
To the best knowledge, ShadowMem represents the first framework to detect and mitigate long-horizon threats using an agentic memory approach, establishing a new paradigm for this critical challenge and opening promising directions for future research.
It is proved that under evidential contracts with conservative fallback, social-only rounds cannot increase confidence and cannot generate purely conformity-driven wrong-but-sure cascades, and it is demonstrated that sound enforcement yields epistemic accountability.
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Our most capable vision-language-action model enhances robot dexterity, reliability, and safety
A Blog post by Ai2 on Hugging Face
A Blog post by IBM Research on Hugging Face
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
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