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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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Engineering Preprint PDF DOI

LaST-R1: Reinforcing Action via Adaptive Physical Latent Reasoning for VLA Models

Hao Chen, Jiaming Liu, Zhonghao Yan, Nuowei Han, Renrui Zhang, Chenyang Gu, Jialin Gao, Ziyu Guo, Siyuan Qian, Yinxi Wang, Peng Jia, Chi-Wing Fu, Shanghang Zhang, Pheng-Ann Heng ยท 2026

Vision-Language-Action (VLA) models have increasingly incorporated reasoning mechanisms for complex robotic manipulation. However, existing approaches share a critical limitation: whether employing exโ€ฆ

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Physics Preprint PDF DOI

Uniaxial strain-driven ferroelastic domain control in LaAlO3

Matthias Roeper, Robin Buschbeck, Jakob Wetzel, Tobias Ritschel, Anna-Lena Hofmann, Vladyslav Kovtunovych, Mike N. Pionteck, Javier Taboada-Gutierrez, Alexey B. Kuzmenko, Martina Basini, Vivek Unikandanunni, Iuliia Kiseleva, Jochen Geck, Susanne C. Kehr, Maximilian Lederer, Simone Sanna, Lukas M. Eng, Samuel D. Seddon ยท 2026

Multiferroic domain walls in functional oxides exhibit properties distinct from the bulk and are increasingly exploited as active elements in nanoelectronic and photonic devices. Deterministic controlโ€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

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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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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Computer Science Preprint PDF DOI

FlashRT: Towards Computationally and Memory Efficient Red-Teaming for Prompt Injection and Knowledge Corruption

Yanting Wang, Chenlong Yin, Ying Chen, Jinyuan Jia ยท 2026

Long-context large language models (LLMs)-for example, Gemini-3.1-Pro and Qwen-3.5-are widely used to empower many real-world applications, such as retrieval-augmented generation, autonomous agents, aโ€ฆ

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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 ยท 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 stimโ€ฆ

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Computer Science Preprint PDF DOI

Index-Assisted Stratified Sampling for Online Aggregation

Yunnan Yu, Zhuoyue Zhao ยท 2026

Ad-hoc queries over frequently updated data in a flat schema are common in real-time data analysis applications and often require very low latency. Online aggregation can achieve so by providing approโ€ฆ

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AI & Data Science Preprint PDF DOI

Normativity and Productivism: Ableist Intelligence? A Degrowth Analysis of AI Sign Language Translation Tools for Deaf People

Nina Seron-Abouelfadil, Poppy Fynes ยท 2026

Sign languages, of any geographical or accentual variation, understandably face continuous scrutiny under the ever present popularity of verbal dictation and audism. Through this, many potential problโ€ฆ

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Engineering Preprint PDF DOI

FreeOcc: Training-Free Embodied Open-Vocabulary Occupancy Prediction

Zeyu Jiang, Changqing Zhou, Xingxing Zuo, Changhao Chen ยท 2026

Existing learning-based occupancy prediction methods rely on large-scale 3D annotations and generalize poorly across environments. We present FreeOcc, a training-free framework for open-vocabulary occโ€ฆ

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Mathematics Preprint PDF DOI

A Scaled Gradient Modified Non-monotone Line Search Method for Constrained Optimization Problems

Qamrul Hasan Ansari, Feeroz Babu, D. R. Sahu, Jen Chih Yao ยท 2026

In this paper, we propose a scaled gradient modified non-monotone line search method for solving constrained minimization problems, and explore several specific properties of this method, namely, its โ€ฆ

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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 ยท 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 doeโ€ฆ

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Computer Science Preprint PDF DOI

Towards Neuro-symbolic Causal Rule Synthesis, Verification, and Evaluation Grounded in Legal and Safety Principles

Zainab Rehan, Christian Medeiros Adriano, Sona Ghahremani, Holger Giese ยท 2026

Rule-based systems remain central in safety-critical domains but often struggle with scalability, brittleness, and goal misspecification. These limitations can lead to reward hacking and failures in fโ€ฆ

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AI & Data Science Preprint PDF DOI

Characterizing the Consistency of the Emergent Misalignment Persona

Anietta Weckauff, Yuchen Zhang, Maksym Andriushchenko ยท 2026

Fine-tuning large language models (LLMs) on narrowly misaligned data generalizes to broadly misaligned behavior, a phenomenon termed emergent misalignment (EM). While prior work has found a correlatioโ€ฆ

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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 ยท 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 iโ€ฆ

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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 ยท 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,โ€ฆ

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AI & Data Science Preprint PDF DOI

RHyVE: Competence-Aware Verification and Phase-Aware Deployment for LLM-Generated Reward Hypotheses

Feiyu Wu, Xu Zheng, Zhuocheng Wang, Yi ming Dai, Hui Li ยท 2026

Large language models (LLMs) make reward design in reinforcement learning substantially more scalable, but generated rewards are not automatically reliable training objectives. Existing work has focusโ€ฆ

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AI & Data Science Preprint PDF DOI

Agent-Agnostic Evaluation of SQL Accuracy in Production Text-to-SQL Systems

Taslim Jamal Arif, Kuldeep Singh ยท 2026

Text-to-SQL (T2SQL) evaluation in production environments poses fundamental challenges that existing benchmarks do not address. Current evaluation methodologies whether rule-based SQL matching or scheโ€ฆ

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