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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 · 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 tha…

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AI & Data Science Preprint PDF DOI

FiLMMeD: Feature-wise Linear Modulation for Cross-Problem Multi-Depot Vehicle Routing

Arthur Correa, Paulo Nascimento, Samuel Moniz · 2026

Solving practical multi-depot vehicle routing problems (MDVRP) is a challenging optimization task central to modern logistics, increasingly driven by e-commerce. To address the MDVRP's computational c…

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Physics Preprint PDF DOI

The faint voice of a radio-weak BL Lacertae: modeling the broadband emission of WISE~J141046.00+740511.2

A. M. Carulli, F. L. Vieyro, M. M. Reynoso, E. J. Marchesini, I. Andruchow · 2026

The WISE source, J141046.00+740511.2, has been recently observed from radio to $\gamma$ rays. Although the optical spectrum is consistent with a BL Lacertae (BL Lac) object, the source displays unusua…

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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 · 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 main…

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AI & Data Science Preprint PDF DOI

Models Recall What They Violate: Constraint Adherence in Multi-Turn LLM Ideation

Garvin Kruthof · 2026

When researchers iteratively refine ideas with large language models, do the models preserve fidelity to the original objective? We introduce DriftBench, a benchmark for evaluating constraint adherenc…

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AI & Data Science Preprint PDF DOI

FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting

Fengxian Ji, Jingpu Yang, Zirui Song, Yuanxi Wang, Zhexuan Cui, Yuke Li, Qian Jiang, Xiuying Chen · 2026

Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluations offer limited coverage, imprecise target-st…

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AI & Data Science Preprint PDF DOI

ClimateVID -- Social Media Videos Analysis and Challenges Involved

Shiqi Xu, Moritz Burmester, Katharina Prasse, Isaac Bravo, Stefanie Walter, Margret Keuper · 2026

The pervasive growth of digital content, specifically short videos on social media platforms, has significantly altered how topics are discussed and understood in public discourse. In this work, we ad…

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AI & Data Science Preprint PDF DOI

DPN-LE: Dual Personality Neuron Localization and Editing for Large Language Models

Lifan Zheng, Xue Yang, Jiawei Chen, Chenyan Wu, Jingyuan Zhang, Fanheng Kong, Xinyi Zeng, Xiang Chen, Yu Tian · 2026

With the widespread adoption of large language models (LLMs), understanding their personality representation mechanisms has become critical. As a novel paradigm in Personality Editing, most existing m…

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AI & Data Science Preprint PDF DOI

HiMix: Hierarchical Artifact-aware Mixup for Generalized Synthetic Image Detection

Shuchang Zhou, Kaiwen Shen, Jiwei Wei, Yuyang Zhou, Peng Wang, Yang Yang · 2026

The rapid evolution of generative models has enabled the creation of highly realistic and diverse synthetic images, posing significant challenges to reliable and generalizable Synthetic Image Detectio…

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AI & Data Science Preprint PDF DOI

Frequency-Aware Semantic Fusion with Gated Injection for AI-generated Image Detection

Shuchang Zhou, Shangkun Wu, Jiwei Wei, Ke Liu, Ran Ran, Caiyan Qin, Yang Yang · 2026

AI-generated images are becoming increasingly realistic and diverse, posing significant challenges for generalizable detection. While Vision Foundation Models (VFMs) provide rich semantic representati…

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AI & Data Science Preprint PDF DOI

Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning

Yuhua Wang, Qinnan Zhang, Xiaodong Li, Huan Zhang, Yifan Sun, Wangjie Qiu, Hainan Zhang, Yongxin Tong, Zhiming Zheng · 2026

Prototype-based Personalized Federated Learning (ProtoPFL) enables efficient multi-domain adaptation by communicating compact class prototypes, but directly sharing them poses privacy risks. A common …

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Computer Science Preprint PDF DOI

AME-PIM: Can Memory be Your Next Tensor Accelerator?

Emanuele Venieri, Simone Manoni, Alberto Florian, Jaehyun Park, Kyomin Sohn, Andrea Bartolini · 2026

High Bandwidth Memory with Processing-in-Memory (HBM-PIM) offers an opportunity to reduce data movement by executing computation directly inside memory, but current commercial platforms expose limited…

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AI & Data Science Preprint PDF DOI

Post-Optimization Adaptive Rank Allocation for LoRA

Vishnuprasadh Kumaravelu, Sunil Gupta, P. K. Srijith · 2026

Exponential growth in the scale of modern foundation models has led to the widespread adoption of Low-Rank Adaptation (LoRA) as a parameter-efficient fine-tuning technique. However, standard LoRA impl…

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Computer Science Preprint PDF DOI

Multifaceted Hero Developers and Bug-Fixing Outcomes Across Severity

Amit Kumar, Mahen Gandhi, Meher Bhardwaj, Hrishikesh Ethari, Sonali Agarwal · 2026

Open-source projects often rely on a small group of highly active contributors known as hero developers. Prior work shows that hero developers are common in many OSS and enterprise projects, yet who q…

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Computer Science Preprint PDF DOI

Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation

Jiaju Chen, Chongming Gao, Chenxiao Fan, Haoyan Liu, Qingpeng Cai, Peng Jiang, Xiangnan He · 2026

Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To accelerate inference without changing the target d…

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Computer Science Preprint PDF DOI

LLM-as-a-Judge for Human-AI Co-Creation: A Reliability-Aware Evaluation Framework for Coding

Md Faizul Ibne Amin, Yutaka Watanobe, Daniel M. Muepu, Haruto Suzuki, Kenta Nanaumi, Md Mostafizer Rahman · 2026

LLMs are increasingly employed both as judges for evaluating open-ended outputs and as co-creation partners in AI-assisted programming; yet rigorous evaluation in human-AI co-creation settings remains…

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Physics Preprint PDF DOI

Neuronal arithmetic operators based on Ovonic threshold switches (OTS) for biologically inspired analog computing

Jingyeong Hwang, Jaesang Lee, Jiin Bang, Younghyun Lee, Unhyeon Kang, Seungmin Oh, Kyungmin Lee, Jaehyun Park, Seongsik Park, Hyun Jae Jang, Sangbum Kim, Min Hyuk Park, Suyoun Lee · 2026

Biological neurons perform arithmetic computations - including additive integration and divisive gain modulation - through synaptic conductance changes and shunting inhibition, enabling context-depend…

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AI & Data Science Preprint PDF DOI

Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework

Zhenzhou Jin, Li You, Xiang-Gen Xia, Xiqi Gao · 2026

Channel fingerprint (CF) is considered a key enabler for facilitating the acquisition of channel state information (CSI) in massive multiple-input multiple-output (MIMO) communication systems. In this…

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Physics Preprint PDF DOI

A benchmark for binary star interaction with a supermassive black hole in general relativity

Megha Sharma, Alexander Heger, Daniel J. Price, Emilio Tejeda, Evgeni Grishin, Luis A. Manzaneda, Alessandro A. Trani · 2026

Most galaxies have supermassive black holes (SMBH) at their centres, surrounded by stars with binary systems also present in this environment. We use two schemes - post-Newtonian (PN) and a scalar per…

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Mathematics Preprint PDF DOI

On the minimum number of maximal distance-$k$ independent sets in trees

Dmitrii Taletskii · 2026

A vertex subset of a graph is called a distance-$k$ independent set if the distance between any two of its distinct vertices is at least $k + 1$. For all $n,k \geq 1$, we determine the minimum possibl…

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