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AI & Data Science Preprint PDF

From Stochastic to Deterministic: A Multi-Criteria Decision Analysis Framework for Bounded Semantic Parsing in AI-Driven Recruitment Screening

A. H. Syed ยท 2026

The tension between automation and accuracy sits at the heart of modern talent acquisition. Recruiters need swiftness. Organisations need secure, auditable decisions. And candidatesโ€”often talented indโ€ฆ

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AI & Data Science Preprint PDF DOI

HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation

Xin Zhou, Dingkang Liang, Xiwu Chen, Feiyang Tan, Dingyuan Zhang, Hengshuang Zhao, Xiang Bai ยท 2026

Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominantly focus on future scene generation, often overlโ€ฆ

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Physics Preprint PDF DOI

Chemical Taxonomy of $\omega$~Centauri: Ten Populations Reveal a Multi-Phase Enrichment History

Furkan Akbaba, Olcay Plevne, Timur Sahin, Sena Aleyna Senturk ยท 2026

$\omega$~Centauri, the most massive globular cluster in the Milky Way, exhibits a level of stellar population complexity that has long resisted a unified chemical characterisation. We exploit high-resโ€ฆ

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AI & Data Science Preprint PDF DOI

Generalizable Sparse-View 3D Reconstruction from Unconstrained Images

Vinayak Gupta, Chih-Hao Lin, Shenlong Wang, Anand Bhattad, Jia-Bin Huang ยท 2026

Reconstructing 3D scenes from sparse, unposed images remains challenging under real-world conditions with varying illumination and transient occlusions. Existing methods rely on scene-specific optimizโ€ฆ

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AI & Data Science Preprint PDF DOI

Representation Fr\'echet Loss for Visual Generation

Jiawei Yang, Zhengyang Geng, Xuan Ju, Yonglong Tian, Yue Wang ยท 2026

We show that Fr\'echet Distance (FD), long considered impractical as a training objective, can in fact be effectively optimized in the representation space. Our idea is simple: decouple the populationโ€ฆ

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AI & Data Science Preprint PDF DOI

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

Keming Wu, Zuhao Yang, Kaichen Zhang, Shizun Wang, Haowei Zhu, Sicong Leng, Zhongyu Yang, Qijie Wang, Sudong Wang, Ziting Wang, Zili Wang, Hui Zhang, Haonan Wang, Hang Zhou, Yifan Pu, Xingxuan Li, Fangneng Zhan, Bo Li, Lidong Bing, Yuxin Song, Ziwei Liu, Wenhu Chen, Jingdong Wang, Xinchao Wang, Xiaojuan Qi, Shijian Lu, Bin Wang ยท 2026

Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning, persistent state, โ€ฆ

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AI & Data Science Preprint PDF DOI

Exploration Hacking: Can LLMs Learn to Resist RL Training?

Eyon Jang, Damon Falck, Joschka Braun, Nathalie Kirch, Achu Menon, Perusha Moodley, Scott Emmons, Roland S. Zimmermann, David Lindner ยท 2026

Reinforcement learning (RL) has become essential to the post-training of large language models (LLMs) for reasoning, agentic capabilities and alignment. Successful RL relies on sufficient exploration โ€ฆ

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AI & Data Science Preprint PDF DOI

Synthetic Computers at Scale for Long-Horizon Productivity Simulation

Tao Ge, Baolin Peng, Hao Cheng, Jianfeng Gao ยท 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 contentโ€ฆ

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AI & Data Science Preprint PDF DOI

An adaptive wavelet-based PINN for problems with localized high-magnitude source

Himanshu Pandey, Ratikanta Behera ยท 2026

In recent years, physics-informed neural networks (PINNs) have gained significant attention for solving differential equations, although they suffer from two fundamental limitations, namely, spectral โ€ฆ

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AI & Data Science Preprint PDF DOI

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 ยท 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 localizationโ€ฆ

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AI & Data Science Preprint PDF DOI

LLM as Clinical Graph Structure Refiner: Enhancing Representation Learning in EEG Seizure Diagnosis

Lincan Li, Zheng Chen, Yushun Dong ยท 2026

Electroencephalogram (EEG) signals are vital for automated seizure detection, but their inherent noise makes robust representation learning challenging. Existing graph construction methods, whether coโ€ฆ

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AI & Data Science Preprint PDF DOI

AEGIS: A Holistic Benchmark for Evaluating Forensic Analysis of AI-Generated Academic Images

Bo Zhang, Tzu-Yen Ma, Zichen Tang, Junpeng Ding, Zirui Wang, Yizhuo Zhao, Peilin Gao, Zijie Xi, Zixin Ding, Haiyang Sun, Haocheng Gao, Yuan Liu, Liangjia Wang, Yiling Huang, Yujie Wang, Yuyue Zhang, Ronghui Xi, Yuanze Li, Jiacheng Liu, Zhongjun Yang, Haihong E ยท 2026

We introduce AEGIS, A holistic benchmark for Evaluating forensic analysis of AI-Generated academic ImageS. Compared to existing benchmarks, AEGIS features three key advances: (1) Domain-Specific Complโ€ฆ

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Physics Preprint PDF DOI

Defending Quantum Classifiers against Adversarial Perturbations through Quantum Autoencoders

Emma Andrews, Sahan Sanjaya, Prabhat Mishra ยท 2026

Machine learning models can learn from data samples to carry out various tasks efficiently. When data samples are adversarially manipulated, such as by insertion of carefully crafted noise, it can cauโ€ฆ

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AI & Data Science Preprint PDF DOI

Strait: Perceiving Priority and Interference in ML Inference Serving

Haidong Zhao, Nikolaos Georgantas ยท 2026

Machine learning (ML) inference serving systems host deep neural network (DNN) models and schedule incoming inference requests across deployed GPUs. However, limited support for task prioritization anโ€ฆ

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AI & Data Science Preprint PDF DOI

Action Motifs: Self-Supervised Hierarchical Representation of Human Body Movements

Genki Kinoshita, Shu Nakamura, Ryo Kawahara, Shohei Nobuhara, Yasutomo Kawanishi, Ko Nishino ยท 2026

Effective human behavior modeling requires a representation of the human body movement that capitalizes on its compositionality. We propose a hierarchical representation consisting of Action Atoms thaโ€ฆ

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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 ยท 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 unโ€ฆ

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Physics Preprint PDF DOI

Mapping the Phase Diagram of the Vicsek Model with Machine Learning

Grace T. Bai, Brandon B. Le ยท 2026

In this study, we use machine learning to classify and interpolate the phase structure of the Vicsek flocking model across the three-dimensional parameter space $(\eta,\rho,v_0)$. We construct a datasโ€ฆ

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Physics Preprint PDF DOI

Deeply virtual pion production through two-loop order

Wen Chen, Feng Feng, Yu Jia, Qing-Tao Song, Guang Tang, Zhe-Yu Wang ยท 2026

Deeply virtual meson production (DVMP) is among the most prominent channels to extract the nucleon's generalized parton distributions (GPDs) at $ep$ scattering facilities such as {\tt JLab} and the upโ€ฆ

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Engineering Preprint PDF DOI

Sequential Inference for Gaussian Processes: A Signal Processing Perspective

Daniel Waxman, Fernando Llorente, Petar M. Djuric ยท 2026

The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support theโ€ฆ

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Engineering Preprint PDF DOI

RopeDreamer: A Kinematic Recurrent State Space Model for Dynamics of Flexible Deformable Linear Objects

Tim Missal, Lucas Domingues, Berk Guler, Simon Manschitz, Jan Peters, Paula Dornhofer Paro Costa ยท 2026

The robotic manipulation of Deformable Linear Objects (DLOs) is a fundamental challenge due to the high-dimensional, non-linear dynamics of flexible structures and the complexity of maintaining topoloโ€ฆ

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