AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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8,685 papers
Across twelve models, dense and hybrid, the authors move a hidden state from one story into another where the two routes lead to different places, and read off which place the model gives, which makes the answer a handoff.
The USAI-Quant benchmark is developed, the first benchmark designed to quantitatively evaluate VLM's reasoning capabilities on built environment metrics via remote sensing imagery, and reveals that current state-of-the-art models consistently fall short on numeric reasoning tasks.
OpenTumorBoard is introduced, a benchmark with 611 patient cases and 19,157 discussion turns across ten specialist roles, transcribed from 12,534 minutes of publicly available tumor board recordings on YouTube, and automated curation pipeline is released to support the development and evaluation of LLMs for multidiscip...
KV-Lingo can be used for seamless model switching, staying close to re-prefill across repeated switches in the authors' multi-turn evaluations, and is found particularly useful for dynamic model routing.
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HERO-MoE, Historical Expert ROuting with Scale-Preserving Fusion, a routing framework that injects historical routing priors into MoE routers by reusing detached, dense routing distributions collected from preceding MoE layers by reusing detached, dense routing distributions collected from preceding MoE layers.
Reinforcement learning (RL) for code agents often uses executable tests to provide binary rewards. With these rewards, Group Relative Policy Optimization (GRPO) assigns identical advantages to test-passing trajectories within each rollout group, overlooking differences in implementation quality and adherence to task re...
A new concept for designing corporate knowledge bases is proposed that integrates the probabilistic vector space of a corporate vocabulary, reflect-ing industry specifics, subject focus, terminology, and culture, with traditional ontological modeling, and enables the efficient extraction of knowledge from accumulated c...
Results show why reflection strategies should be assessed separately on final performance, parent improvement and calibration-to-test transfer.
Direct Preference Optimization (DPO) aligns language models by optimizing over sequence-level sums of token-wise implicit reward differences. However, we identify a pervasive pathology in this formulation: a disproportionately small subset of high-frequency token types dominates cumulative sequence scores while appeari...
Overall, the results show that targeted feature quality depends jointly on the model signal and estimator, with detection and intervention capturing complementary properties.
LT-OPD, a training framework for extreme visual-token reduction, is proposed and it is shown that on-policy learning can substantially recover capabilities lost to extreme visual-token reduction.
Agents that answer questions from compressed or retrieved memory must recognize when the evidence a query needs is no longer in memory. Benchmarks for this task usually create insufficient-evidence examples by deleting supporting passages. We show that this construction leaks the label through memory size: on MuSiQue,...
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.
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
A Blog post by Liquid AI on Hugging Face
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