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3,686 papers
Global objectives, such as KL divergence and ELBO, are widely used in Bayesian inference for measuring distributional discrepancy. This paper studies distributional ``local-mass behaviours'' that are not directly captured by such global objectives. We introduce and use two mathematical tools: (1) Mass Index for recordi...
Large Language Models (LLMs) are increasingly used for zero-shot annotation and LLM-as-a-judge tasks, yet their reliability hinges on how model-internalized priors interact with user-provided instructions. We investigate three dimensions of this interaction: (1) how an LLM's familiarity with data and task definitions r...
Deep networks on the symmetric positive-definite (SPD) manifold promise expressive representations by encoding data geometry as an inductive bias, but stacking BiMap layers with the standard ReEig nonlinearity often adds no capacity: on real, preconditioned EEG data, ReEig rarely activates, so the stack behaves as a si...
We introduce AREX, a training-free sampler for pretrained flow matching models that uses the target mean and covariance to capture an analytically tractable part of the sampling dynamics. We show that the velocity field of the moment-matched Gaussian target is the $L^2$-optimal affine approximation to the marginal velo...
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We study fixed-confidence best-arm identification under strict 1-bit feedback constraints. At each round, the learner selects an arm and a query set, and receives only a single bit indicating whether the sampled reward belongs to that set. We consider a distribution-free finite-variance setting with arm-wise localizati...
The results demonstrate that flow matching naturally adapts to the intrinsic geometry of data and mitigates the curse of dimensionality, as the convergence exponent depends on the intrinsic rather than ambient dimension.
Why does supervised fine-tuning (SFT) lead to more forgetting than reinforcement fine-tuning (RFT), even when all teacher demonstrations are semantically correct? We study this question on classification tasks where tokens within each semantic class express the same semantic answer in different styles. The tasks share...
Many scientific questions require reasoning about what was never observed: What if the conditions, interventions, or history had been different? Models can predict accurately on observed data yet fail on such what-if queries when correlated inputs are varied independently. A common remedy is to add controlled simulatio...
Replication materials accompanying “The marginal value of alternative data in credit screening: Evidence from Chinese digital lending” by Yuan Chen and Jiawei Xu. The package contains instructions for obtaining the source data, environment specifications, data processing and modelling scripts, parameter settings, rando...
This study describes the formulation and in vitro evaluation of FERTI-MAX, a proprietary extender developed through iterative, osmolality-guided optimization to approximate the osmotic and pH environment of chicken seminal plasma. Successive prototypes were narrowed from an initial hypertonic range of approximately 520...
This study describes the formulation and in vitro evaluation of FERTI-MAX, a proprietary extender developed through iterative, osmolality-guided optimization to approximate the osmotic and pH environment of chicken seminal plasma. Successive prototypes were narrowed from an initial hypertonic range of approximately 520...
The present study was conducted from May 2023 to August 2024 at the Rashtriya Krishi Vikas Yojana (RKVY) backyard poultry farm, Faculty of Veterinary and Animal Sciences, Barkachha, Mirzapur, Uttar Pradesh, India, to assess the influence of meteorological conditions on fertility, hatchability, and embryonic mortality i...
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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