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3,686 papers
A Graph-based Faithful sTep-level credit-assignment framework (GRAFT) that grafts all rollout trajectories into a trajectory graph, recovering node state-values via Bellman iteration on the graph, and assigning credit to each edge by the node value difference is proposed.
**A field-level audit of one month of retraction deposits (v2)** Author: Trafalgar Law (independent). Data pulled from the public Crossref REST API on 2026-09-23. Sample and reproduction query included. This is a metadata audit, not an accusation against any publisher or author. ## Why On 2026-09-19 the record for a fi...
Simultaneous Latent Budget Trees, a probabilistic machine learning framework for classification trees in the presence of a stratification factor such as a temporal, spatial, or demographic variable, acting as a control variable or potential confounder, is introduced.
Probability-floor samplers substantially narrow the blind spot, demonstrating that the choice of truncation criterion matters for retaining human-used tokens and motivate decoding methods that preserve contextually appropriate low-probability choices while maintaining generation quality.
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This work discretizes the spectral representation directly, preserving the correlation structure among spectral weights without requiring probability assumptions, and yields an efficient low-rank approximation that is positive semi-definite by construction and consistent under mild regularity conditions.
This article provides a unifying review of recent diffusion-based methods for generative lossy compression, with a focus on image compression, and highlights the role of common randomness and connections to inverse problems, and identifies open challenges.
This paper applies various NLP techniques to demonstrate feature de-biasing, feature compression, and industry classification in the commercial insurance context to show that NLP is not merely a supplementary tool but a foundational element of modern, data-driven insurance analytics.
A quantum reservoir processing framework that captures a broad range of physical computing models with quantum systems and it is numerically demonstrated that exponential concentration can still exist even with a physical reservoir such as an Ising model whenever the reservoir operates in a quantum-chaotic phase.
This paper develops theory for deep neural network (DNN) estimators under dependent data. To provide theory applicable to a variety of DNN-based estimators, I first establish nonasymptotic probability bounds on the theoretical and empirical $\mathcal{L}^{2}$-errors of nonparametric sieve estimators for a general class...
A faster implementation of mixtures of Manly transformations is proposed, which uses Newton's method for optimization in an EM gradient algorithm instead of Nelder-Mead in a traditional EM.
Recursive models show promise on reasoning and language tasks, yet their test-time scaling lacks a principled criterion for selecting trajectories or determining recurrent depth. We introduce \textbf{Energy-guided Recursive Model (ERM)}, which uses Hopfield-type memories of valid local and global structures to assign i...
The lift is proposed, which replaces the free latent weight by a learnable slack plus an unconstrained network---the body---that takes a permutation-invariant summary of the training batch as input and couples to the gradient formed on it.
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
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Health & Bioscience
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Data Mining & Modeling
GPT-Lab
· gpt-lab.eu
Nov 3, 2026
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
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