AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
4,920 papers
X-FED is proposed, a novel Conflict-Aware Cross-Client Federated Exit Distillation framework that jointly addresses both client- and depth-wise conflicts while extending PFL to early-exit networks and introduces a client-decoupled formulation that reduces communication overhead with theoretical soundness.
BAFA, the Bounded Active Fairness Auditor is introduced, the Bounded Active Fairness Auditor for query-efficient auditing of black-box LLMs, suggesting that active sampling can reduce resources needed for independent fairness auditing with LLMs, supporting continuous model evaluations.
This paper formalizes KV management as a causal system of three primitives: KV Admission, Selection, and Eviction, and instantiate KV Admission via Write-Gated KV (WG-KV), a lightweight mechanism that learns to predict token utility before cache entry.
Kascade is a training-free sparse attention method that leverages known observations such as 1) post-softmax attention is intrinsically sparse, and 2) the identity of high-weight keys is stable across nearby layers to achieve high accuracy on long-context LLM inference.
Reach audiences
Advertise in front of researchers, engineers, and readers.
It is found that explicit world-modeling yields better representations in terms of higher probing accuracy and steerability of the model, and that better representations yield larger gains from GRPO, especially on harder cube states.
ScalePRM, which scales verification compute as an alternative to ground-truth supervision for training process reward models, generates multiple independent verifications of each reasoning step and aggregate their judgments to produce synthetic step-level labels without ground truth.
To further accelerate speculative decoding in long-context generation, SpecPV is introduced, a self-speculative decoding approach that performs fast verification using partial key-value states (KV) and periodically applies full verification to eliminate accumulated errors.
This work shows that the multiplicity within a large Rashomon set enables reactive robustness and increases information leakage, and highlights the dual role of Rashomon sets as both a resource and a risk for trustworthy ML.
A curiosity-driven quantized Mixture-of-Experts framework that addresses both accuracy and stability through Bayesian epistemic uncertainty-based routing across heterogeneous experts, suitable for safety-sensitive edge deployments where both accuracy and predictability are critical.
By reframing DODE as a sequential decision-making problem, this approach addresses the credit assignment challenge through a learned policy and provides a novel framework for calibration of microscopic traffic simulations.
A structure-preserving PINN framework for the nonlinear KdV equation, a prototypical model for nonlinear and dispersive wave propagation, that embeds the conservation of mass and Hamiltonian energy directly into the loss function, ensuring physically consistent and energy-stable evolution throughout training and prediction.
A cross-fidelity knowledge distillation and adaptive fusion network (CFKD-AFN), which leverages abundant but low-fidelity simulation data to enhance the prediction on scarce but high-fidelity trial data, and is extended to an interpretable variant for exploratory analysis of feature-attribution patterns associated with treatment outcomes.
Education Innovation
Machine Intelligence
A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.
General Science
GPT-Lab
· gpt-lab.eu
Sep 3, 2026
Adaptive AI agents can help make BIM data more machine-readable by navigating IFC models, interpreting inconsistent information, and mapping it to defined standards. In this blog, Alok Rawat shares findings from a real-world pilot in construction workflows. The post Adaptive AI Agents in Construction Workflows appeared first on GPT-Lab.
Climate & Sustainability
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
