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🔍 neil olver 📂 AI & Data Science
Showing 88687 results for "neil olver" in AI & Data Science
AI & Data Science Preprint PDF DOI

Synthetic Computers at Scale for Long-Horizon Productivity Simulation

Tao Ge, Baolin Peng, Hao Cheng, Jianfeng Gao · 2026

Realistic long-horizon productivity work is strongly conditioned on user-specific computer environments, where much of the work context is stored and organized through directory structures and content…

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Stop Holding Your Breath: CT-Informed Gaussian Splatting for Dynamic Bronchoscopy

Andrea Dunn Beltran, Daniel Rho, Aarav Mehta, Xinqi Xiong, Raul San Jose Estepar, Ron Alterovitz, Marc Niethammer, Roni Sengupta · 2026

Bronchoscopic navigation relies on registering endoscopic video to a preoperative CT scan, but respiratory motion deforms the airway by 5-20 mm, creating CT-to-body divergence that limits localization…

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AI & Data Science Preprint PDF DOI

PhyCo: Learning Controllable Physical Priors for Generative Motion

Sriram Narayanan, Ziyu Jiang, Srinivasa Narasimhan, Manmohan Chandraker · 2026

Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic rebound, and material responses seldom match their un…

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AI & Data Science Preprint PDF DOI

Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

Yujun Wu, Dongxu Zhang, Xinchen Li, Jinhang Xu, Yiling Duan, Yumou Liu, Jiabao Pan, Xuanhe Zhou, Jingxuan Wei, Siyuan Li, Jintao Chen, Conghui He, Cheng Tan · 2026

Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of methodological evolution. In particular, it does not…

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AI & Data Science Preprint PDF DOI

On the Proper Treatment of Units in Surprisal Theory

Samuel Kiegeland, Vesteinn Sn{ae}bjarnarson, Tim Vieira, Ryan Cotterell · 2026

Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a unit underspecified. In practice, experimental stim…

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AI & Data Science Preprint PDF DOI

PRISM: Pre-alignment via Black-box On-policy Distillation for Multimodal Reinforcement Learning

Sudong Wang, Weiquan Huang, Xiaomin Yu, Zuhao Yang, Hehai Lin, Keming Wu, Chaojun Xiao, Chen Chen, Wenxuan Wang, Beier Zhu, Yunjian Zhang, Chengwei Qin · 2026

The standard post-training recipe for large multimodal models (LMMs) applies supervised fine-tuning (SFT) on curated demonstrations followed by reinforcement learning with verifiable rewards (RLVR). H…

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AI & Data Science Preprint PDF DOI

Splitting Argumentation Frameworks with Collective Attacks and Supports

Matti Berthold, Lydia Blumel, Giovanni Buraglio, Anna Rapberger · 2026

This work proposes novel splitting techniques for argumentation formalisms that incorporate supports between defeasible elements. We base our studies on bipolar set-based argumentation frameworks (BSA…

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AI & Data Science Preprint PDF DOI

Neural Aided Kalman Filtering for UAV State Estimation in Degraded Sensing Environments

Akhil Gupta, Erhan Guven · 2026

Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracking of adversarial unmanned aerial vehicles (UAVs…

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AI & Data Science Preprint PDF DOI

UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentation

Shuokun Cheng, Jinghao Shi, Kun Sun · 2026

Accurate lesion segmentation is crucial for clinical diagnosis and treatment planning. However, lesions often resemble surrounding tissues and exhibit ill-defined boundaries, leading to unstable predi…

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AI & Data Science Preprint PDF DOI

What Makes a Good Terminal-Agent Benchmark Task: A Guideline for Adversarial, Difficult, and Legible Evaluation Design

Ivan Bercovich · 2026

Terminal-agent benchmarks have become a primary signal for measuring the coding and system-administration capabilities of large language models. As the market for evaluation environments grows, so doe…

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AI & Data Science Preprint PDF DOI

AesRM: Improving Video Aesthetics with Expert-Level Feedback

Yujin Han, Yujie Wei, Yefei He, Xinyu Liu, Tianle Li, Zichao Yu, Andi Han, Shiwei Zhang, Tingyu Weng, Difan Zou · 2026

Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyond visual fidelity. …

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AI & Data Science Preprint PDF DOI

TopBench: A Benchmark for Implicit Prediction and Reasoning over Tabular Question Answering

An-Yang Ji, Jun-Peng Jiang, De-Chuan Zhan, Han-Jia Ye · 2026

Large Language Models (LLMs) have advanced Table Question Answering, where most queries can be answered by extracting information or simple aggregation. However, a common class of real-world queries i…

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AI & Data Science Preprint PDF DOI

Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling

Ansar Aynetdinov, Patrick Haller, Alan Akbik · 2026

Recent research has shown that filtering massive English web corpora into high-quality subsets significantly improves training efficiency. However, for high-resource non-English languages like German,…

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AI & Data Science Preprint PDF DOI

Faster 3D Gaussian Splatting Convergence via Structure-Aware Densification

Linjie Lyu, Ayush Tewari, Jianchun Chen, Thomas Leimkuhler, Christian Theobalt · 2026

3D Gaussian Splatting has emerged as a powerful scene representation for real-time novel-view synthesis. However, its standard adaptive density control relies on screen-space positional gradients, whi…

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Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning

Jingcheng Deng, Zihao Wei, Liang Pang, Junhong Wu, Shicheng Xu, Zenghao Duan, Huawei Shen · 2026

Latent reasoning offers a more efficient alternative to explicit reasoning by compressing intermediate reasoning into continuous representations and substantially shortening reasoning chains. However,…

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AI & Data Science Preprint PDF DOI

Exploring Interaction Paradigms for LLM Agents in Scientific Visualization

Jackson Vonderhorst, Kuangshi Ai, Haichao Miao, Shusen Liu, Chaoli Wang · 2026

This paper examines how different types of large language model (LLM) agents perform on scientific visualization (SciVis) tasks, where users generate visualization workflows from natural-language inst…

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AI & Data Science Preprint PDF DOI

Differentiable latent structure discovery for interpretable forecasting in clinical time series

Ivan Lerner, Jean Feydy, Alexandre Kalimouttou, Anita Burgun, Francis Bach · 2026

Background: Timely, uncertainty-aware forecasting from irregular electronic health records (EHR) can support critical-care decisions, yet most approaches either impute to a grid or sacrifice interpret…

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AI & Data Science Preprint PDF DOI

Splitting Assumption-Based Argumentation Frameworks

Giovanni Buraglio, Wolfgang Dvorak, Stefan Woltran · 2026

Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. However, the high computational complexity of core rea…

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AI & Data Science Preprint PDF DOI

Language Models Refine Mechanical Linkage Designs Through Symbolic Reflection and Modular Optimisation

Joao Pedro Gandarela, Thiago Rios, Stefan Menzel, Andre Freitas · 2026

Designing mechanical linkages involves combinatorial topology selection and continuous parameter fitting. We show that language models can systematically improve linkage designs through symbolic repre…

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AI & Data Science Preprint PDF DOI

LLMs as ASP Programmers: Self-Correction Enables Task-Agnostic Nonmonotonic Reasoning

Adam Ishay, Joohyung Lee · 2026

Recent large language models (LLMs) have achieved impressive reasoning milestones but continue to struggle with high computational costs, logical inconsistencies, and sharp performance degradation on …

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