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Showing 378930 results for "program evaluation"
AI & Data Science Preprint PDF DOI

Negative Ontology of True Target for Machine Learning: Towards Evaluation and Learning under Democratic Supervision

Yongquan Yang ยท 2026

This article philosophically examines how shifts in assumptions regarding the existence and non-existence of the true target (TT) give rise to new perspectives and insights for machine learning (ML)-bโ€ฆ

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Physics Preprint PDF DOI

A Measure-Theoretic Transport Formulation of Galaxy Evolution on the Galaxy Manifold: Geometric Constraints

Tsutomu T. Takeuchi ยท 2026

We develop a measure-theoretic framework for galaxy evolution in which galaxy populations are described as probability measures on a state space. Galaxy evolution is represented as the time evolution โ€ฆ

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Mathematics Preprint PDF DOI

The Main Problem of Block Theory: Picky Elements and Subnormalizers

Alexander Moreto ยท 2026

This article is essentially an English translation of a paper of mine, published in \emph{La Gaceta de la RSME}. Its aim is to present, for a broad mathematical audience, a research programme in localโ€ฆ

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Computer Science Preprint PDF DOI

Mono2Sls: Automated Monolith-to-Serverless Migration via Multi-Stage Pipeline with Static Analysis

Xingyan Chen, Yuxin Su, Zishan Su, Yang Yu, Zibin Zheng ยท 2026

Cloud computing platforms offer elastic scaling, managed infrastructure, and pay-per-use pricing, but moving existing monolithic backends to them remains a difficult software engineering task. In pracโ€ฆ

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AI & Data Science Preprint PDF DOI

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator

Alessio Sordo, Lingxiao Du, Meeka-Hanna Lenisa, Evgeny Bogdanov, Maxim Romanovsky ยท 2026

The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific evaluation datasets; however, the collection of suchโ€ฆ

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Computer Science Preprint PDF DOI

Counterexample-Guided Interval Weakening

Ben M. Andrew, Louise A. Dennis, Michael Fisher, Marie Farrell ยท 2026

Systems deployed for long periods of time in dynamic environments may experience performance degradation that affects timing guarantees, even when their functional behaviour remains unchanged. In the โ€ฆ

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AI & Data Science Preprint PDF DOI

Stochastic simultaneous optimistic optimization

Michal Valko, Alexandra Carpentier, Remi Munos ยท 2026

We study the problem of global maximization of a function f given a finite number of evaluations perturbed by noise. We consider a very weak assumption on the function, namely that it is locally smootโ€ฆ

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Computer Science Preprint PDF DOI

Private Private Information in Second-Price Auction

Boyu Liu, Wei Tang, Zihe Wang, Shuo Zhang ยท 2026

Classic results show that even an arbitrarily small correlation across bidders' information can enable full surplus extraction in auctions and related mechanism design settings. Motivated by this fragโ€ฆ

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AI & Data Science Preprint PDF DOI

Interoceptive machine framework: Toward interoception-inspired regulatory architectures in artificial intelligence

Diego Candia-Rivera (NERV) ยท 2026

This review proposes an integrative framework grounded on interoception and embodied AI-termed the interoceptive machine framework-that translates biologically inspired principles of internal-state reโ€ฆ

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Physics Preprint PDF DOI

Tests of scalar polarizations with multi-messenger events

Sk Md Adil Imam, Macarena Lagos ยท 2026

Gravitational wave (GW) observations provide a unique opportunity to test Einstein's General Relativity (GR) in the strong-field regime. While GR predicts only two tensor polarization modes, generic mโ€ฆ

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Computer Science Preprint PDF DOI

Understanding the Limits of Automated Evaluation for Code Review Bots in Practice

Veli Karakaya, Utku Boran Torun, Baykal Mehmet Ucar, Eray Tuzun ยท 2026

Automated code review (ACR) bots are increasingly used in industrial software development to assist developers during pull request (PR) review. As adoption grows, a key challenge is how to evaluate thโ€ฆ

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AI & Data Science Preprint PDF DOI

Point Cloud Registration for Fusion between SPECT MPI and CTA Images

Ni Yao, Xiangyu Liu, Shaojie Tang, Danyang Sun, Chuang Han, Yanting Li, Jiaofen Nan, Chengyang Li, Fubao Zhu, Chen Zhao, Zhihui Xu, Weihua Zhou ยท 2026

Clinical fusion of Single Photon Emission Computed Tomography Myocardial Perfusion Imaging (SPECT MPI) and Computed Tomography Angiography (CTA) remains limited by cross-modality misregistration and rโ€ฆ

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Physics Preprint PDF DOI

StarCLR: Contrastive Learning Representation for Astronomical Light Curves

Junyao Ding, Xiaodian Chen, Xinyi Gao, Xiaoyu Tang, Shu Wang, Yang Huang, Xinyu Qi, Guirong Xue, Ali Luo, Jifeng Liu ยท 2026

With the rapid development of time-domain surveys, the availability of massive light curve data offers new opportunities for studying stellar evolution and variable star classification, while simultanโ€ฆ

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AI & Data Science Preprint PDF DOI

SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering

Yuqing Fu, Yimin Deng, Wanyu Wang, Yuhao Wang, Yejing Wang, Hongshi Liu, Yiqi Wang, Xiao Han, Maolin Wang, Guoshuai Zhao, Yi Chang, Xiangyu Zhao ยท 2026

Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reasoning paths in response to the complex user queriโ€ฆ

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AI & Data Science Preprint PDF DOI

MIMIC: A Generative Multimodal Foundation Model for Biomolecules

Siavash Golkar, Jake Kovalic, Irina Espejo Morales, Samuel Sledzieski, Minhuan Li, Ksenia Sokolova, Geraud Krawezik, Alberto Bietti, Claudia Skok Gibbs, Roman Klypa, Shengwei Xiong, Francois Lanusse, Liam Parker, Kyunghyun Cho, Miles Cranmer, Tom Hehir, Michael McCabe, Lucas Meyer, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Helen Qu, Jeff Shen, David Fouhey, Hadi Sotoudeh, Vikram Mulligan, Pilar Cossio, Sonya M. Hanson, Alisha N. Jones, Olga G. Troyanskaya, Shirley Ho ยท 2026

Biological function emerges from coupled constraints across sequence, structure, regulation, evolution, and cellular context, yet most foundation models in biology are trained within one modality or fโ€ฆ

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Computer Science Preprint PDF DOI

Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora

Chenkai Pan, Xinglong Xu, Yuhang Xu, Yujun Wu, Siyuan Li, Jintao Chen, Conghui He, Jingxuan Wei, Cheng Tan ยท 2026

Reliably transferring specialized human knowledge from text into large language models remains a fundamental challenge in artificial intelligence. Fine-tuning on domain corpora has enabled substantialโ€ฆ

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Mathematics Preprint PDF DOI

On Maximal Symmetries of Toric Varieties over Fields of Characteristic Zero

Yutaro Naito ยท 2026

In this paper, we study complete simplicial toric varieties admitting faithful actions of large symmetric groups. First, we correct a recent classification result by Esser, Ji, and Moraga concerning $โ€ฆ

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AI & Data Science Preprint PDF DOI

Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI

Parampuneet Kaur Thind, Vaibhav Katturu, Giacomo Zema, Roberto Del Prete ยท 2026

Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, including neural architecture search (NAS) guided by โ€ฆ

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Computer Science Preprint PDF DOI

Scalable First-Order Interior Point Trust Region Algorithms for Linearly Constrained Optimization

Yuexin Su, Chenyi Zhang, Peiyuan Huang, Tongyang Li, Yinyu Ye ยท 2026

Computing approximate Karush--Kuhn--Tucker (KKT) points for constrained nonconvex programs is a fundamental problem in mathematical programming. Interior-point trust-region (IPTR) methods are particulโ€ฆ

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Engineering Preprint PDF DOI

Comparative Evaluation of Modern Deep Learning Methodologies for Portfolio Optimization

Samuel Ozechi, Banjo Francis, Wisdom Yakanu, Joe Wayne Byers ยท 2026

This study proposes a portfolio optimization framework that integrates advanced deep learning architectures with traditional financial models to enhance risk-adjusted performance. Using historical datโ€ฆ

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