AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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9,261 papers
We establish sharp degree bounds for Putinar sum-of-squares (SOS) certificates in terms of the positivity margin $\delta$. For any fixed Archimedean quadratic module with prescribed generators and any fixed degree bound on the objective, normalized polynomial objectives admit a uniform certificate-degree upper bound of...
AI systems may miss indirect, culturally situated distress or provide support mismatched to the application context. Existing benchmarks do not jointly address cultural variation, application context, and practitioner disagreement. We introduce VEILED-SH, a benchmark and construction methodology for evaluating single-t...
Agents now act on the Web, publishing packages, models and datasets through registry APIs, and remembering past verifications spares them the work. But a verdict rests on premises. When a signing key is revoked, everything built on it stops passing, yet the advisory names only the key, and the old verdicts of its depen...
It is shown that, under a sufficiently large but practical candidate pool, embedding recall exhibits diminishing returns, motivating a closer examination of reranker quality, and support evaluating the retrieval and reranking stages separately when selecting an optimization target for industrial retrieval systems.
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Where does the novelty a base language model produces with no task come from, and what can an LLM judge of a long stream actually see? We dismantle a cognitively inspired generation loop over 24 conditions on three base models. Most of its effect lives in one operation: a new subject injected every few hundred tokens (...
This work introduces Mimir, a 1.78B-parameter language model based on the Hierarchical Reasoning Model Text (HRM-Text) architecture, a recurrent-depth transformer whose layers are split into a low-level and high-level stack that are applied repeatedly in an interleaved schedule.
We introduce GRAB, a constructor-encoder-bridge pipeline for table question answering. Our method lifts relational data into an heterogeneous graph, encodes it via message passing, and transfers the signals to an LLM through a small set of query-conditioned latent tokens. This provides the LLM with a compact, task-rele...
Benchmark scores often misrepresent a large language model's (LLM's) knowledge, because they rely, e.g., on the model's ability to follow specific formatting requirements. This especially penalizes base models that may know the correct answers but lack the ability -- typically introduced in post-training -- to structur...
Diffusion language models (DLMs) have emerged as the leading non-autoregressive alternative to language modeling. Because their likelihoods are intractable, generative perplexity (gen-PPL) has become the de facto standard for reporting unconditional generation quality. We analyze why gen-PPL is unreliable as a measure...
Multilingual speech foundation models claim broad language coverage, but how well they handle spontaneous African speech, and how best to adapt them, remains unclear. We benchmark zero-shot and fine-tuned speech recognition on the WAXAL corpus of spontaneous speech in 19 African languages, covering Whisper, MMS, Omnili...
We introduce CARTE (Culturally Anchored Regional-Territorial Evaluation), a multiple-choice benchmark for evaluating the ability of large language models (LLMs) to discriminate fine grained, geographically grounded and regionally differentiated knowledge within France. While prior benchmarks focus on national-level cul...
An activation oracle is a language model trained to convert the activations of another model into natural language. However, it is so far unclear to what extent these verbalizations are calibrated. Crucially, the oracle's verbalization come without any measure of confidence. Here, we compare five methods for estimating...
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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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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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