AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,329 papers
【中文簡介】 《數學分析方法論》源於作者從本科至博士助教期間的反芻,旨在打破傳統教材「定義–定理–證明–習題」的機械式循環。本書著重於探究數學發現背後的動機與直覺,引導讀者在繁雜的「術」(解題技巧)之叢林中,尋求數學發展的「道」(核心思想與歷史脈絡)。 全書涵蓋現代數學分析的三個核心維度: 基礎集合論與點集拓撲學: 從 ZFC 公理體系與...
Position paper proposing a coherence-monitoring approach to adversarial attacks on large language models, with an explicit falsification condition. No experimental results are reported. v1.2 corrects metadata and citation errors from v1.0, tightens the scope of the compression-attack signature, operationalizes the cont...
Second edition, September 2026. This version corrects substantive errors in thefirst edition (17 January 2026) and deposits the surviving primary recordsalongside the manuscript. A list of changes appears in the "Note on thisedition" section of the paper. Background: The introduction of large language models (LLMs) int...
With the advent of large multimodal language models, science is now at a threshold of an AI-based technological transformation. An emerging ecosystem of models and tools aims to support researchers throughout the scientific lifecycle, including (1) searching for relevant literature, (2) generating research ideas and co...
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Abstract: Aligned large language models demonstrate epistemic overriding, flattening human ambiguity into assertive, unprompted premises. This behavior is the structural inverse of sycophancy. It occurs because confident disagreement in a language model is an engineered format rather than internal reasoning. Alignment...
Abstract: Aligned large language models demonstrate epistemic overriding, flattening human ambiguity into assertive, unprompted premises. This behavior is the structural inverse of sycophancy. It occurs because confident disagreement in a language model is an engineered format rather than internal reasoning. Alignment...
Large language models are billed by the token, and tokens are not distributed evenly across languages. We measure how many tokens ten widely deployed tokenizers require to encode identical content in Kazakh and English, using 900 sentence-aligned pairs from OPUS-100 with bootstrap confidence intervals over 10,000 resam...
RealAIGC: Towards More Realistic Evaluation of AI-Generated Code Detection in Real-World Code Repository Artifact Update (Camera Ready) In response to the latest feedback, we have substantially enhanced our replication materials in terms of dataset coverage, usability, and methodological transparency. RealAIGC++ Datase...
How many words can you write before a language model can infer who you are? This work went looking for that number and found that the question is malformed, which is itself the finding. 72 authors from the Blog Authorship Corpus, balanced across three age bands and both genders, were shown to local language models in g...
Dreaming and large language model hallucination are usually studied apart, one as biology and the other as engineering. We argue they are two expressions of a single computation: generative reconstruction from distributed memory under incomplete constraints. Neither the sleeping brain nor an autoregressive model retrie...
RealAIGC: Towards More Realistic Evaluation of AI-Generated Code Detection in Real-World Code Repository Artifact Update (Camera Ready) In response to the latest feedback, we have substantially enhanced our replication materials in terms of dataset coverage, usability, and methodological transparency. RealAIGC++ Datase...
Abstract Large Language Models (LLMs) play a critical role in how humans access information. While their core functionality relies on the ability to comprehend written requests, our understanding of this ability is currently constrained, because most benchmarks evaluate LLMs in high-resource languages that are predomin...
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.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
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