AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
9,568 papers
This paper recast context compression as a causal decision preservation problem over discrete interaction units and introduces FOCUS, a training-free context compression framework that operates entirely at test time that requires no offline data collection or fine-tuning.
Users of language-based assistive agents often make ambiguous requests. In response, an assistant can either directly act on its interpretation of the request --- risking misalignment with the user --- or ask a clarifying question. Which option is the most safe and helpful? A common approach is to ask questions that mi...
On-policy distillation, where a student learns from a stronger teacher's feedback on its own outputs, is a common way to pass reasoning to smaller models. We analyze what it transfers at small scale, distilling Qwen3-8B into Qwen3 4B, 1.7B and 0.6B students, in thinking mode (reason at length, then end the reasoning an...
An agent that uses tools typically responds to what the user explicitly asks, yet completing the task may require information the user never requested. Work on proactive agents mainly studies whether and when an agent should act on its own, not what information it should pursue. We study a distinct axis of proactivity:...
Reach audiences
Advertise in front of researchers, engineers, and readers.
CoEM preserves potentially useful source excerpts verbatim in a pending set, allowing subsequent context to clarify their relevance before irreversible compression, and consistently improves long-context reasoning.
This work introduces a preference-oriented benchmark and systematically characterize the capabilities and limitations of personal agents associated with these three dimensions of harness evolution, offering a unified perspective on the limits of personalization through harness evolution and inform future harness design...
This work proposes self-instructing policy optimization (SIPO) with a contrastive self-teacher to provide dense credit, and demonstrates that SIPO outperforms both RLVR and OPSD baselines without an external teacher or additional generation.
LibraryDesignBench is introduced, a two-phase benchmark in which an agent implements a full-featured library from a specification that defines required capabilities and potential use cases without prescribing the design.
Pretrained transformers use little of their depth to follow references in context. Thirteen base models reliably follow only 1.4-3.6 lines, and extra pretrained loops add little. A task-trained rank-8 LoRA at one early layer extends this computation with all model weights frozen. Qwen3-8B improves from 15.5% to 99% exa...
The Optimal Transport-based Robust Off-Policy Evaluation (OTROPE) is proposed, a likelihood-free evaluation that performs distributional correction in a semantic space via optimal transport to align labeled behavior-policy samples with unlabeled target-policy samples, yielding a doubly robust-style evaluation.
REST (REpresentation-Supervised Thoughts), a training objective that turns four properties of a valid thought representation into differentiable losses added to CE, instantiate in latent single-agent and multi-agent systems, without architectural changes or added parameters at inference.
GeoOutageBench provides a design principle and foundation for assessing LLM-KG systems that support real-world infrastructure resilience analysis and provides user-configurable evaluation of three important, highly coherent yet less studied tasks.
Natural Language Processing
Our most capable vision-language-action model enhances robot dexterity, reliability, and safety
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.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
