AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
9,261 papers
A realizable hard-label construction confirms that higher spectral diversity can coexist with worse distribution recovery even under equal member energies and nonnegative correlations, and the consensus direction retains $\gamma_{\mathrm{co}}=43.8\%$, $33.7\%$, and $35.9\%$ of centered residual variance.
This work takes inspiration from a resource-rational perspective on human cognition and introduces a novel GRPO reward that encourages efficient reasoning about whether the task contains all the information needed to solve it, leading to human-like abstention performance gains.
A structural dependency theorem is proved: under any schedule fixed in advance and non-decreasing, no emitted token can depend on input that has not yet arrived, and extends to unbounded streams under arbitrary asynchronous arrival.
VISPATH, a visual-intent-guided path reasoning framework for MM-KGQA, is proposed and constructed, a benchmark for evaluating multimodal multi-hop reasoning over KGs, covering questions that require two to four hops over KG paths.
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work evaluates 21 representative models, including large language models, vision-language models, time-series language models, and physiological signal foundation models under three complementary settings, and shows that none of the evaluated models achieves consistently strong performance across physiological sig...
We study when limiting what a language model can see improves learning. We compare standard CoT, the more general learner that reads the full trace, with recursive language models, which restricts itself by solving each subtask in an isolated context. In-distribution, this generality comes for free: CoT can efficiently...
A three-stage pipeline for speakers from India, Indonesia, and Latin America achieves 80-85% entity recall, 76-86% filler recall, and 6-10% WER across 6k test utterances, outperforming Whisper and a commercial ASR on entity recall while matching a zero-shot 30B model with 10x fewer parameters.
Current radiology report generation (RRG) models usually produce descriptive reports based on a single examination or only the most recent prior examination, limiting their ability to perform accurate and meaningful longitudinal comparisons and detect subtle interval changes. Although recent approaches have begun to in...
Clinical predictive models often rely on structured Electronic Health Record data, such as time-series and procedure codes. While recent approaches have begun leveraging unstructured clinical notes, they typically encode them as flat sequences, which may lose explicit relational and temporal structure present in clinic...
Gating the value pathway of attention reportedly improves language model pretraining, and prior studies disagree on why. We argue and provide experimental evidence that such gates supply two different things that softmax attention lacks: abstention and noise filtering. The first is abstention, which allows an attention...
A Python library that connects fairness research on language models through explicit declarations of model capabilities and input requirements, so that compatible components can be combined, methods compared under a common protocol, and workflows extended to new models and datasets.
Sixteen language models drawn from ten families produced, on average, the semantic diversity of 1.69 distinct formulations of a psychotherapeutic case, against a single-model baseline of 1.43 from one model's own runs. Ensembles place more than one reading before a decision-maker on the premise that several models supp...
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.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
