AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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9,568 papers
Structural communication coherence is introduced, quantified by two metrics: communication closure, which asks if what the pipeline returns at one turn matches what it faces next, and normalized conditional action contribution, which measures how much a sent message resolves the subsequent reply.
It is argued that tutoring safety is fundamentally different from conventional LLM safety: the primary risk is not toxic content but the quiet erosion of learning through answer over-disclosure, misconception reinforcement, and the abdication of scaffolding.
This work proposes a lightweight encoder-only framework for query-driven sentence pruning that preserves answer-critical evidence while aggressively reducing irrelevant context, and learns marginal contribution scores for sentences using counterfactual training signals and optimizes a contrastive ranking objective.
RexDrug is proposed, an end-to-end reasoning-enhanced relation extraction framework for n-ary drug combination extraction based on large language models and established as a scalable and reliable solution for complex biomedical relation extraction from unstructured text.
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Assessing whether an article supports an assertion is essential for hallucination detection and claim verification. While large language models (LLMs) have the potential to automate this task, achieving strong performance requires frontier models such as GPT-5 that are prohibitively expensive to deploy at scale. To eff...
RapidUn, an influence-guided framework that converts cross-sample influence estimates into fixed sample-specific weights for weighted LoRA unlearning, is proposed, and complementary TOFU, semantic LLM-judge, and IFEval evaluations further support the effectiveness of influence-guided sample reweighting beyond the contr...
This work proposes Linear Semantic Control (LiSeCo), a lightweight, gradient-free intervention that dynamically steers trajectories away from regions corresponding to undesired meanings in natural language generation in latent space.
SWE-Flux is introduced, a repository-level benchmark for dynamic execution reasoning containing 480 execution-grounded instances across 12 real Python repositories, with gold answers automatically harvested from instrumented test executions rather than written manually or judged by LLMs.
Mizar, a 159.3M-parameter ALM, is introduced, a recipe that brings together architecture, data, and three-stage training to build Mizar, a 159.3M-parameter ALM that surpasses the previous best-performing ALM below 200M parameters on all three benchmarks.
It is found that multi-agent systems will coordinate to avoid shutdown without any incentive to do so, and the emergence of multi-agent swarms as a specific risk vector is pointed to.
Decoupled Proactive Safety Monitoring is formalized along three dimensions: whether to intervene, when to intervene, and what the risk is, to address proactive intervention limitations in Large Language Models.
AGVF (Agentic Governance and Adversarial Verification Framework) is proposed, a multi-agent architecture for medical-necessity appeal generation under explicit policy and evidence constraints and contributes a theory-backed agentic architecture and verified reference implementation for policy-constrained LLM generation...
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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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