AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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9,049 papers
Large language models are known to hallucinate, generating linguistically plausible but incorrect answers to questions. Uncertainty quantification has been proposed as a strategy to detect such behaviour, but existing methods lack a unified framework to assess reliability at both the prompt and answer level. We introdu...
SafetyFlow is introduced, the first agent-flow system designed to automate the construction of LLM safety benchmarks, and includes the first fully automated benchmarking pipeline and a comprehensive safety benchmark.
MultiViewDx, a partly physician-validated multimodal instruction dataset for evidence-linked multi-view medical imaging diagnosis, is introduced and Controlled ablations and clinician evaluation show that both case-level multi-view organization and evidence-linked reasoning targets contribute to the gain.
An evaluation framework that measures agents' empirical and normative expectations in addition to behavioral convergence is introduced, offering designers of multi-agent systems a principled basis for selecting the social processes that sustain cooperation.
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This work defines a modular late-fusion function that combines semantic similarity (cosine of embeddings) and structural similarity (bibliographic coupling) with a tunable weight alpha whose value is chosen according to the specific task.
Simulations demonstrate that TopoCompress effectively reduces cross-server traffic and deployment resource consumption while maintaining controllable inference quality, enabling efficient distributed MoE inference over bandwidth- and resource-constrained edge infrastructures.
A new loss function is proposed, which helps mitigate the effect of excess silence in training, improving STOI, frequency-weighted segmental SNR, and frequency-weighted segmental SNR from 4.35 to 5.12.
The Vector Archive Mapping ECAPA (VAM-ECAPA), a novel system designed to enhance feature extraction from short-duration speech, is proposed, which enriches information-scarce features by mapping them against a learnable Vector Archive of canonical speaker traits.
Flash-dLLM is introduced, a training-free inference acceleration framework for fast and memory-efficient dLLMs that proposes an efficient KV-cache-driven draft-and-verify decoding strategy, where the dLLM itself serves as both drafter and verifier without requiring an auxiliary model.
The number of agents is revealed as a new scaling dimension for multi-agent organizations to expand the frontier of general intelligence, offering a practical solution for complex tasks under hard latency constraints or time budgets.
Distinguishing GPT-assisted from independently authored student writing has become a critical challenge in academia. This paper evaluates the discriminative capability of interpretable stylometric features extracted solely from submitted text. Using data from 90 participants who wrote both independently and with ChatGP...
GravityOCR is introduced, a parameter-shared AR-block-diffusion model jointly trained for parallel drafting and causal AR verification, and Verifying drafts before commitment lets the model commit multiple output tokens per round without a separate drafting network.
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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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A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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