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AI & Data Science Preprint PDF DOI

Hard to Be Heard: Phoneme-Level ASR Analysis of Phonologically Complex, Low-Resource Endangered Languages

V.S.D.S.Mahesh Akavarapu, Michael Daniel, Gerhard Jager ยท 2026

We present a phoneme-level analysis of automatic speech recognition (ASR) for two low-resourced and phonologically complex East Caucasian languages, Archi and Rutul, based on curated and standardized โ€ฆ

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Physics Preprint PDF DOI

Leading UV divergences of quantum corrections to K\"ahler superpotential in general $\mathcal{N}=1$ chiral model

R.M. Iakhibbaev, A. I. Mukhaeva, D.M. Tolkachev ยท 2026

Using the Bogoliubov-Parasiuk theorem we derive differential equations for the sum of leading UV divergences of the K\"ahler potential in the general $\mathcal{N}=1$ supersymmetric chiral theory. The โ€ฆ

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Computer Science Preprint PDF DOI

How Do People Accept Robot in Public Space? A Cross-Cultural Study in Germany and Japan

Zhe Zeng, Clara Ayumi Fechner, Fei Yan, Hailong Liu ยท 2026

With the increasing deployment of robots in public spaces, encounters between robots and incidentally copresent persons (InCoPs) are becoming more frequent. However, InCoPs remain largely underexploreโ€ฆ

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Computer Science Preprint PDF DOI

Audio-DeepThinker: Progressive Reasoning-Aware Reinforcement Learning for High-Quality Chain-of-Thought Emergence in Audio Language Models

Xiang He, Chenxing Li, Jinting Wang, Yan Rong, Tianxin Xie, Wenfu Wang, Li Liu, Dong Yu ยท 2026

Large Audio-Language Models (LALMs) have made significant progress in audio understanding, yet they primarily operate as perception-and-answer systems without explicit reasoning processes. Existing meโ€ฆ

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AI & Data Science Preprint PDF DOI

CanonSLR: Canonical-View Guided Multi-View Continuous Sign Language Recognition

Xu Wang, Shengeng Tang, Wan Jiang, Yaxiong Wang, Lechao Cheng, Richang Hong ยท 2026

Continuous Sign Language Recognition (CSLR) has achieved remarkable progress in recent years; however, most existing methods are developed under single-view settings and thus remain insufficiently robโ€ฆ

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AI & Data Science Preprint PDF DOI

QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning

Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, Huan-Yu Liu, Cheng Xue, Xiao-Fan Xu, Han Fang, Yang Yang, Yu-Chun Wu, Guo-Ping Guo, Zhao-Yun Chen ยท 2026

Large language models (LLMs) show strong capabilities in general reasoning but typically lack reliability in scientific domains like quantum mechanics, which demand strict adherence to physical constrโ€ฆ

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Computer Science Preprint PDF DOI

VerilogCL: A Contrastive Learning Framework for Robust LLM-Based Verilog Generation

Yan Tan, Tong Liu, Xiangchen Meng, Yangdi Lyu ยท 2026

Large Language Models (LLMs) have recently achieved strong performance in software code generation. However, applying them to hardware description languages (HDLs), such as Verilog, remains challenginโ€ฆ

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AI & Data Science Preprint PDF DOI

Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients?

Ku Onoda, Paavo Parmas, Manato Yaguchi, Yutaka Matsuo ยท 2026

In policy gradient reinforcement learning, access to a differentiable model enables 1st-order gradient estimation that accelerates learning compared to relying solely on derivative-free 0th-order estiโ€ฆ

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AI & Data Science Preprint PDF DOI

mlr3torch: A Deep Learning Framework in R based on mlr3 and torch

Sebastian Fischer, Lukas Burk, Carson Zhang, Bernd Bischl, Martin Binder ยท 2026

Deep learning (DL) has become a cornerstone of modern machine learning (ML) praxis. We introduce the R package mlr3torch, which is an extensible DL framework for the mlr3 ecosystem. It is built upon tโ€ฆ

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AI & Data Science Preprint PDF DOI

Attention-ResUNet for Automated Fetal Head Segmentation

Ammar Bhilwarawala, Mainak Bandyopadhyay ยท 2026

Automated fetal head segmentation in ultrasound images is critical for accurate biometric measurements in prenatal care. While existing deep learning approaches have achieved a reasonable performance,โ€ฆ

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Computer Science Preprint PDF DOI

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations

Yunjia Xi, Menghui Zhu, Jianghao Lin, Bo Chen, Ruiming Tang, Yong Yu, Weinan Zhang ยท 2026

Recently, large language models (LLMs) have advanced recommendation systems (RSs), and recent works have begun to explore how to integrate LLMs into industrial RSs. While most approaches deploy LLMs oโ€ฆ

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AI & Data Science Preprint PDF DOI

Distributional Off-Policy Evaluation with Deep Quantile Process Regression

Qi Kuang, Chao Wang, Yuling Jiao, Fan Zhou ยท 2026

This paper investigates the off-policy evaluation (OPE) problem from a distributional perspective. Rather than focusing solely on the expectation of the total return, as in most existing OPE methods, โ€ฆ

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Engineering Preprint PDF DOI

Frugal Geofencing via Energy-aware Sensing and Reporting

David E. Ruiz-Guirola, Miltiadis Filippou, Onel A. Lopez ยท 2026

Timely and accurate monitoring in geofencing scenarios is challenging when relying on ultra-low power Internet of Things devices (IoTDs) powered by energy harvesting (EH). This is mainly because frequโ€ฆ

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Computer Science Preprint PDF DOI

AQPIM: Breaking the PIM Capacity Wall for LLMs with In-Memory Activation Quantization

Kosuke Matsushima, Yasuyuki Okoshi, Masato Motomura, Daichi Fujiki ยท 2026

Processing-in-Memory (PIM) architectures offer a promising solution to the memory bottlenecks in data-intensive machine learning, yet often overlook the growing challenge of activation memory footprinโ€ฆ

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AI & Data Science Preprint PDF DOI

Rabies diagnosis in low-data settings: A comparative study on the impact of data augmentation and transfer learning

Khalil Akremi, Mariem Handous, Zied Bouslama, Farah Bassalah, Maryem Jebali, Mariem Hanachi, Ines Abdeljaoued-Tej ยท 2026

Rabies remains a major public health concern across many African and Asian countries, where accurate diagnosis is critical for effective epidemiological surveillance. The gold standard diagnostic methโ€ฆ

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AI & Data Science Preprint PDF DOI

Can LLM-Generated Text Empower Surgical Vision-Language Pre-training?

Chengan Che, Chao Wang, Jiayuan Huang, Xinyue Chen, Luis C. Garcia-Peraza-Herrera ยท 2026

Recent advancements in self-supervised learning have led to powerful surgical vision encoders capable of spatiotemporal understanding. However, extending these visual foundations to multi-modal reasonโ€ฆ

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AI & Data Science Preprint PDF DOI

ConventionPlay: Capability-Limited Training for Robust Ad-Hoc Collaboration

Abhishek Sriraman, Eleni Vasilaki, Robert Loftin ยท 2026

Ad-hoc collaboration often relies on identifying and adhering to shared conventions. However, when partners can follow multiple conventions, agents must do more than simply adapt; they must actively sโ€ฆ

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AI & Data Science Preprint PDF DOI

Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents

Akriti Jain, Anish Mulay, Divyansh Verma, Aishani Pandey, Pritika Ramu, Aparna Garimella ยท 2026

Decision-making is a cognitively intensive task that requires synthesizing relevant information from multiple unstructured sources, weighing competing factors, and incorporating subjective user preferโ€ฆ

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AI & Data Science Preprint PDF DOI

Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Models

Zehua Zang, Xi Wang, Fuchun Sun, Xiao Xu, Lixiang Lium, Jiahuan Zhou, Jiangmeng Li ยท 2026

Vision-Language-Action models (VLAs) achieve remarkable performance in sequential decision-making but remain fragile to subtle environmental shifts, such as small changes in object pose. We attribute โ€ฆ

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Engineering Preprint PDF DOI

NIM4-ASR: Towards Efficient, Robust, and Customizable Real-Time LLM-Based ASR

Yuan Xie, Jiaqi Song, Guang Qiu, Xianliang Wang, Kai Qiao, Junfeng Yuan, Shengqing Liu, Yi Zhang, Bowen Chen, Ming Lei, Jie Gao, Jie Wu ยท 2026

Integrating large language models (LLMs) into automatic speech recognition (ASR) has become a mainstream paradigm in recent years. Although existing LLM-based ASR models demonstrate impressive performโ€ฆ

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