Category
5,133 papers
Experimental results demonstrate that the proposed uncertainty-aware replay buffer enables an RL agent to obtain higher rewards during training compared to other existing uncertainty-aware RL frameworks.
A scalable bandit-based system that optimizes product page layouts in real time while preserving human control over design intent, providing a scalable path toward learning-to-design the web.
An architecture search framework that makes the alignment between experts and the structure of the data an explicit search variable and ensures that the assignment of data clusters to experts is optimised jointly with the per-expert architectures is proposed.
PruneShift, an evaluation framework that separates broad predictive fidelity, fidelity near selector outputs, and the quality of the selected pruning decision, is introduced, showing why predictive fit, decision reliability, and pruning method quality require separate evidence.
Reach audiences
Advertise in front of researchers, engineers, and readers.
The first complex augmented Broad Learning System (CA-BLS) is introduced, which transforms real-valued inputs into phase-encoded complex representations and adopts widely linear modeling to jointly leverage covariance and pseudo-covariance information via complex conjugate augmentation, enabling effective modeling of latent nonlinearities, coherence structures, and second-order dependencies inaccessible to conventional BLS formulations.
GraM-Diff is proposed, a unified classifier-guided Graph-Mamba diffusion framework for EEG synthesis that embeds Graph Convolutional Networks within a diffusion U-Net to model inter-electrode connectivity and Bidirectional Mamba state-space blocks for linear-complexity long-range temporal modeling.
HDR-RoPE is proposed, which extends RoPE from independent 2D rotations to higher-dimensional rotations and introduces a Paley-I orthogonal basis to obtain balanced, isotropic, and dense phase mixing within each rotation subspace and significantly enhances channel coupling and rotational degrees of freedom while maintaining orthogonal stability and the relative position closure property.
An underlying mechanism explaining the gap in uncertainty quantification is identified: path switching, where agents frequently abandon their current search direction in-trajectory, breaking the link between early signal and final outcome.
This work introduces Tabular Synthesis Strategy Designer, which uses an LLM to design synthesis procedures rather than directly generate records, and provides the LLM with tree-derived summaries of variable dependence rather than raw records, which produces Python programs for local execution and evaluation.
A target-centric survey of QAT is provided, aimed at clarifying both its theoretical foundations and its evolving implementation landscape and synthesizing cross-target differences in error characteristics, numerical formats, and strategy transferability.
This work considers one-step generators from an optimal transport view, investigating Wasserstein Gradient Flow (WGF) for modeling smooth and controlled distributional evolution in probability space, and proposes a novel reward-guided fine-tuning of a one-step generative model via WGF.
LLMODE is proposed, a token-efficient framework for irregular spatio-temporal forecasting with a frozen LLM backbone that shows competitive overall performance, with clearer advantages under sparse or dynamically complex irregular sampling.
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.
