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🔍 program development 📂 AI & Data Science
Showing 31717 results for "program development" in AI & Data Science
AI & Data Science Preprint PDF DOI

One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement

Yixiao Zhou, Dongzhou Cheng, zhiliang wu, Yi Yang, Yu Cheng, Hehe Fan · 2026

Large Language Models (LLMs) often fail to utilize their latent reasoning capabilities due to a distributional mismatch between ambiguous human inquiries and the structured logic required for machine …

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AI & Data Science Preprint PDF DOI

Language corpora for the Dutch medical domain

B. van Es · 2026

\textbf{Background:} Dutch medical corpora are scarce, limiting NLP development. \\ \textbf{Methods:} We translated English datasets, identified medical text in generic corpora, and extracted open Dut…

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AI & Data Science Preprint PDF DOI

Multi-action Tangled Program Graphs for Multi-task Reinforcement Learning with Continuous Control

Quentin Vacher (IETR), Nicolas Beuve (IETR), Mickael Dardaillon (IETR), Karol Desnos (IETR) · 2026

Over the past few decades, machine learning has been widely used to learn complex tasks. Reinforcement Learning (RL), inspired by human behavior, is a great example, as it involves developing specific…

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AI & Data Science Preprint PDF DOI

On the use of satellite information to estimate agricultural carbon footprint in a small area framework

Riccardo Pajno, Felicetta Carillo, Paolo Maranzano, Timo Schmid, Riccardo Borgoni · 2026

The agricultural sector is undergoing rapid change due to climate pressures, demographic shifts, and uneven economic development, increasing the demand for reliable environmental indicators at fine sp…

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AI & Data Science Preprint PDF DOI

AutoResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery

Lei Xiong, Kun Luo, Ziyi Xia, Wenbo Zhang, Jin-Ge Yao, Zheng Liu, Jingying Shao, Jianlyu Chen, Hongjin Qian, Xi Yang, Qian Yu, Hao Li, Chen Yue, Xiaan Du, Yuyang Wang, Yesheng Liu, Haiyu Xu, Zhicheng Dou · 2026

Autonomous scientific research is significantly advanced thanks to the development of AI agents. One key step in this process is finding the right scientific literature, whether to explore existing kn…

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AI & Data Science Preprint PDF DOI

ValueAlpha: Agreement-Gated Stress Testing of LLM-Judged Investment Rationales Before Returns Are Observable

Sidi Chang, Peiying Zhu, Yuxiao Chen · 2026

Long-horizon investment decisions create a pre-realization evaluation problem: realized returns are the eventual arbiter of investment quality, but they arrive too late and are too noisy to guide many…

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AI & Data Science Preprint PDF DOI

Training Transformers as a Universal Computer

Ruize Xu, Chenxiao Yang, Yanhong Li, David McAllester · 2026

We demonstrate that a small transformer can learn to execute programs in MicroPy, a simplified yet computationally universal programming language. Given procedure definitions together with an expressi…

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AI & Data Science Preprint PDF DOI

Elite-Driven Support Vector Machines for Classification

Mohammad Jafari Jozani, Bahram Moeinianfar · 2026

Support vector machines (SVMs) are a standard tool for binary classification, but their classical formulations are purely data-driven and offer no direct way to encode trusted benchmark models or stru…

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AI & Data Science Preprint PDF DOI

Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation

Sicheng Dai, Kai Chen, Hongwang Xiao, Shan Yu, Qiwei Ye · 2026

Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically require full fine-tuning on each downstream task indi…

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AI & Data Science Preprint PDF DOI

Doing More With Less: Revisiting the Effectiveness of LLM Pruning for Test-Time Scaling

Ocean Monjur, Shahriar Kabir Nahin, Anshuman Chhabra · 2026

While current Large Language Models (LLMs) exhibit remarkable reasoning capabilities through test-time compute scaling (TTS), their massive parameter counts and high inference costs have motivated the…

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AI & Data Science Preprint PDF DOI

The Dynamics of Delusion: Modeling Bidirectional False Belief Amplification in Human-Chatbot Dialogue

Ashish Mehta, Jared Moore, Jacy Reese Anthis, William Agnew, Eric Lin, Peggy Yin, Desmond C. Ong, Nick Haber, Carol Dweck · 2026

There is growing concern that AI chatbots might fuel delusional beliefs in users. Some have suggested that humans and chatbots mutually reinforce false beliefs over time, but quantitative evidence is …

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AI & Data Science Preprint PDF DOI

Frontier Coding Agents Can Now Implement an AlphaZero Self-Play Machine Learning Pipeline For Connect Four That Performs Comparably to an External Solver

Joshua Sherwood, Ben Aybar, Benjamin Kaplan · 2026

Forecasting when AI systems will become capable of meaningfully accelerating AI research is a central challenge for AI safety. Existing benchmarks measure broad capability growth, but may not provide …

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CiteRadar: A Citation Intelligence Platform for Researcher Profiling and Geographic Visualization

Chenxu Niu, Yiming Sun · 2026

Understanding the geographic reach and community structure of one's scholarly citations is increasingly valuable for career development, grant applications, and collaboration discovery -- yet accessib…

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AI & Data Science Preprint PDF DOI

BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

Ali Keshavarzi, Quentin Bouniot, Benjamin M. Smith, Elsa Angelini · 2026

Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understanding various respiratory diseases. Airway bifur…

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A New Kind of Network? Review and Reference Implementation of Neural Cellular Automata

Martin Spitznagel, Janis Keuper · 2026

Stephen Wolfram proclaimed in his 2003 seminal work "A New Kind Of Science" that simple recursive programs in the form of Cellular Automata (CA) are a promising approach to replace currently used math…

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AI & Data Science Preprint PDF DOI

BenchGuard: Who Guards the Benchmarks? Automated Auditing of LLM Agent Benchmarks

Xinming Tu, Tianze Wang, Yingzhou (Minta) Lu, Kexin Huang, Yuanhao Qu, Sara Mostafavi · 2026

As benchmarks grow in complexity, many apparent agent failures are not failures of the agent at all - they are failures of the benchmark itself: broken specifications, implicit assumptions, and rigid …

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AI & Data Science Preprint PDF DOI

Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence

NVIDIA: Amala Sanjay Deshmukh, Kateryna Chumachenko, Tuomas Rintamaki, Matthieu Le, Tyler Poon, Danial Mohseni Taheri, Ilia Karmanov, Guilin Liu, Jarno Seppanen, Arushi Goel, Mike Ranzinger, Greg Heinrich, Guo Chen, Lukas Voegtle, Philipp Fischer, Timo Roman, Karan Sapra, Collin McCarthy, Shaokun Zhang, Fuxiao Liu, Hanrong Ye, Yi Dong, Mingjie Liu, Yifan Peng, Piotr Zelasko, Zhehuai Chen, Nithin Rao Koluguri, Nune Tadevosyan, Lilit Grigoryan, Ehsan Hosseini Asl, Pritam Biswas, Leili Tavabi, Yuanhang Su, Zhiding Yu, Peter Jin, Alexandre Milesi, Netanel Haber, Yao Xu, Sarah Amiraslani, Nabin Mulepati, Eric Tramel, Jaehun Jung, Ximing Lu, Brandon Cui, Jin Xu, Zhiqi Li, Shihao Wang, Yuanguo Kuang, Shaokun Zhang, Huck Yang, Boyi Li, Hongxu Yin, Song Han, Pavlo Molchanov, Adi Renduchintala, Charles Wang, David Mosallanezhad, Soumye Singhal, Luis Vega, Katherine Cheung, Sreyan Ghosh, Yian Zhang, Alexander Bukharin, Venkat Srinivasan, Johnny Greco, Andre Manoel, Maarten Van Segbroeck, Suseella Panguliri, Rohit Watve, Divyanshu Kakwani, Shubham Pachori, Jeffrey Glick, Radha Sri-Tharan, Aileen Zaman, Khanh Nguyen, Shi Chen, Jiaheng Fang, Qing Miao, Wenfei Zhou, Yu Wang, Zaid Pervaiz Bhat, Varun Praveen, Arihant Jain, Ramanathan Arunachalam, Tomasz Kornuta, Ashton Sharabiani, Amy Shen, Wei Huang, Yi-Fu Wu, Ali Roshan Ghias, Huiying Li, Brian Yu, Nima Tajbakhsh, Chen Cui, Wenwen Gao, Li Ding, Terry Kong, Manoj Kilaru, Anahita Bhiwandiwalla, Marek Wawrzos, Daniel Korzekwa, Pablo Ribalta, Grzegorz Chlebus, Besmira Nushi, Ewa Dobrowolska, Maciej Jakub Mikulski, Kunal Dhawan, Steve Huang, Jagadeesh Balam, Yongqiang Wang, Nikolay Karpov, Valentin Mendelev, George Zelenfroynd, Meline Mkrtchyan, Qing Miao, Omri Almog, Bhavesh Pawar, Rameshwar Shivbhakta, Sudeep Sabnis, Ashrton Sharabiani, Negar Habibi, Geethapriya Venkataramani, Pamela Peng, Prerit Rodney, Serge Panev, Richard Mazzarese, Nicky Liu, Michael Fukuyama, Andrii Skliar, Roger Waleffe, Duncan Riach, Yunheng Zou, Jian Hu, Hao Zhang, Binfeng Xu, Yuhao Yang, Zuhair Ahmed, Alexandre Milesi, Carlo del Mundo, Chad Voegele, Zhiyu Cheng, Nave Assaf, Andrii Skliar, Daniel Afrimi, Natan Bagrov, Ran Zilberstein, Ofri Masad, Eugene Khvedchenia, Natan Bagrov, Borys Tymchenko, Tomer Asida, Daniel Afrimi, Parth Mannan, Victor Cui, Michael Evans, Katherine Luna, Jie Lou, Pinky Xu, Guyue Huang, Negar Habibi, Michael Boone, Pradeep Thalasta, Adeola Adesoba, Dina Yared, Christopher Parisien, Leon Derczynski, Shaona Ghosh, Wes Feely, Micah Schaffer, Radha Sri-Tharan, Jeffrey Glick, Barnaby Simkin, George Zelenfroynd, Tomasz Grzegorzek, Rishabh Garg, Aastha Jhunjhunwala, Sergei Kolchenko, Farzan Memarian, Haran Kumar, Shiv Kumar, Isabel Hulseman, Anjali Shah, Kari Briski, Padmavathy Subramanian, Joey Conway, Udi Karpas, Jane Polak Scowcroft, Annie Surla, Shilpa Ammireddy, Ellie Evans, Jesse Oliver, Tom Balough, Chia-Chih Chen, Sandip Bhaskar, Alejandra Rico, Bardiya Sadeghi, Seph Mard, Katherine Cheung, Meredith Price, Laya Sleiman, Saori Kaji, Wesley Helmholz, Wendy Quan, Michael Lightstone, Jonathan Cohen, Jian Zhang, Oleksii Kuchaiev, Boris Ginsburg, Jan Kautz, Eileen Long, Mohammad Shoeybi, Mostofa Patwary, Oluwatobi Olabiyi, Andrew Tao, Bryan Catanzaro, Udi Karpas · 2026

We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 Nano Omni delivers co…

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AI & Data Science Preprint PDF DOI

A Unifying Framework for Unsupervised Concept Extraction

Chandler Squires, Pradeep Ravikumar · 2026

Techniques for concept extraction, such as sparse autoencoders and transcoders, aim to extract high-level symbolic concepts from low-level nonsymbolic representations. When these extracted concepts ar…

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AI & Data Science Preprint PDF DOI

Learning to Think from Multiple Thinkers

Nirmit Joshi, Roey Magen, Nathan Srebro, Nikolaos Tsilivis, Gal Vardi · 2026

We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different solutions, e.g., step-by-step solutions to math prob…

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AI & Data Science Preprint PDF DOI

SpecRLBench: A Benchmark for Generalization in Specification-Guided Reinforcement Learning

Zijian Guo, Ilker Is{i}k, H. M. Sabbir Ahmad, Wenchao Li · 2026

Specification-guided reinforcement learning (RL) provides a principled framework for encoding complex, temporally extended tasks using formal specifications such as linear temporal logic (LTL). While …

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