AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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9,261 papers
Simple PCA over a model's own decoding variance is thus an effective, low-cost probe of stylistic structure in LLM representations, one that also exposes sharp cross-model differences in how that structure is organized.
Subliminal learning shows that language models can transmit a hidden trait through outputs that appear unrelated to it. One proposed explanation, token entanglement, links animal and number tokens through the model's output vocabulary. Yet existing measurements answer different questions: whether outputs co-vary, fixed...
Unified Latent Diffusion Reasoner improves multimodal reasoning by weaving it into a single thread, where the model predicts successive thoughts in a common representation space.
Psychotherapists need repeated training and supervision; however, scalability is problematic. We present MyMentorLLM, a multimodal voice- and text-based deliberate-practice environment with 2,100 complete Cognitive Behavioural Therapy (CBT) sessions. Each session links a DSM-5-TR-grounded LLM patient (with major depres...
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This work formalizes an attack space and evaluates representative OS defenses using four agent workloads and a Linux telemetry pipeline and shows that the main limitation is not OS observability.
Results show that exact-match recovery of the benchmark-designated rule can underestimate the downstream utility of retrieved benchmark assertions in this setting, and should be evaluated inside the classification loop rather than by exact-match recall alone.
This work proposes a fully local cascade framework that reframes de-identification from open-ended entity recognition to constrained privacy triage, and evaluates three reviewer configurations against same-family LLM-only baselines and a commercial API on math tutoring transcripts from two large platforms.
Formalizing legal provisions promises machine-accessible law and automated legal reasoning, and recent LLMs make it tempting to generate such formalizations directly from statutory text. However, any formalization makes implicit interpretive choices whose consequences are hard to anticipate, especially if an LLM is the...
GenDistill, a multi-stage pipeline for distilling a pretrained Transformer into an efficient Hybrid Kimi Delta Attention (Hybrid-KDA) student, finds that log-likelihood-based evaluation consistently underestimates the gap between teacher and student, and can reverse the ranking of design choices, so conclusions drawn f...
This work analyzes three datasets: ANDROIDS, DAIC-WOZ, E-DAIC and identifies a systematic bias from interviewer prompts in semi-structured interviews that highlights a cross-dataset, architecture-agnostic bias and emphasizes the need for analyses that localize decision evidence by time and speaker to ensure models lear...
Metadata Augmented Private Language Evolution (MAPLE) extracts DP tabular metadata and uses in-context learning to firmly ground the initial synthetic distribution in the target domain, and yields a strictly better privacy-utility trade-off.
Test-time training (TTT) adapts large language models (LLMs) during inference using only unlabeled test inputs. Existing methods, however, face two major bottlenecks on hard reasoning tasks: (1) \emph{lack of learnable samples}, as self-generated pseudo-labels on difficult questions are often noisy and yield unstable r...
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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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