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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

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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Sociology & Anthropology Preprint PDF DOI

Phase Transitions in Economic Inequality:Taxation and Extremal Replacement Dynamics

Lautaro Giordano, Sebastian Goncalves, Jose Roberto Iglesias, Maria Fabiana Laguna ยท 2026

We present a minimal agent-based model of interacting agents characterized by their wealth to study taxation and inequality in a non-conservative economy. Wealth evolves through an extremal stochasticโ€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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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 ยท 2026

Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of methodological evolution. In particular, it does notโ€ฆ

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Engineering Preprint PDF DOI

FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems

Binghao Huang, Yunzhu Li ยท 2026

We present FlexiTac, a low-cost, open-source, and scalable piezoresistive tactile sensing solution designed for robotic end-effectors. FlexiTac is a practical "plug-in" module consisting of (i) thin, โ€ฆ

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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 ยท 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). Hโ€ฆ

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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 ยท 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 (BSAโ€ฆ

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Computer Science Preprint PDF DOI

Tailwind: A Practical Framework for Query Accelerators

Geoffrey X. Yu, Ryan Marcus, Tim Kraska ยท 2026

Relational database management systems (RDBMSes) can process general-purpose queries, but often have lower performance compared to custom-built solutions for specific queries. For example, consider a โ€ฆ

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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 ยท 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. โ€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

PROMISE-AD: Progression-aware Multi-horizon Survival Estimation for Alzheimer's Disease Progression and Dynamic Tracking

Qing Lyu, Jeremy Hudson, Mohammad Kawas, Yuming Jiang, Chenyu You, Christopher T Whitlow ยท 2026

Individualized Alzheimer's disease (AD) progression prediction requires models that use irregular visits, account for censoring, avoid diagnostic leakage, and provide calibrated horizon risks. We propโ€ฆ

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Computer Science Preprint PDF DOI

To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems

Shreya Chappidi, Jatinder Singh ยท 2026

Responsible AI research typically focuses on examining the use and impacts of deployed AI systems. Yet, there is currently limited visibility into the pre-deployment decisions to pursue building such โ€ฆ

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AI & Data Science Preprint PDF DOI

TAFA-GSGC: Group-wise Scalable Point Cloud Geometry Compression with Progressive Residual Refinement

Xiumei Li, Alexander Kopte, Andre Kaup ยท 2026

Scalable compression is essential for bandwidth-adaptive transmission, yet most learned codecs are optimized for a fixed rate-distortion point, making rate adaptation costly due to re-encoding or mainโ€ฆ

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