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arXiv preprints from January 1, 2026 through September 21, 2026 — 18:26:17 EST

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Posted in math.NA · 2026-01-16 · Rishi Mishra, Smriti, Balaji Srinivasan, Sundararajan Natarajan, Ganapathy Krishnamurthi

Exact Constraint Enforcement in Physics-Informed Extreme Learning Machines using Null-Space Projection Framework

Physics-informed extreme learning machines (PIELMs) typically impose boundary and initial conditions through penalty terms, yielding only approximate satisfaction that is sensitive to user-specified weights and can propagate errors into the interior solution. This work introduces Null-Space Projected PIELM (NP-PIELM), achieving exact...

💬 0 commentsarXiv:2601.10999v2PDF
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Posted in cs.DC · 2026-01-16 · Shinsuk Kang, Youngjae Kim

AFLL: Real-time Load Stabilization for MMO Game Servers Based on Circular Causality Learning

Massively Multiplayer Online (MMO) game servers must handle thousands of simultaneous players while maintaining sub-100ms response times. When server load exceeds capacity, traditional approaches either uniformly throttle all message types regardless of importance (damaging gameplay) or apply fixed heuristic rules that fail to adapt...

💬 0 commentsarXiv:2601.10998v2PDF
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Posted in cond-mat.mtrl-sci · 2026-01-16 · Haewon Kim, Taekgi Lee, Seongeun Hong, Kyeong-Ho Kim, Yongchul G. Chung

Data-driven Prediction of Ionic Conductivity in Solid-State Electrolytes with Machine Learning and Large Language Models

Solid-state electrolytes (SSEs) are attractive for next-generation lithium-ion batteries due to improved safety and stability but their low room-temperature ionic conductivity hinders practical application. Experimental synthesis and testing of new SSEs remain time-consuming and resource intensive. Machine learning (ML) offers an...

💬 0 commentsarXiv:2601.10997v2PDF
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Posted in q-fin.PM · 2026-01-16 · Muhammad Abro, Hassan Jaleel

Regret-Driven Portfolios: LLM-Guided Smart Clustering for Optimal Allocation

We attempt to mitigate the persistent tradeoff between risk and return in medium- to long-term portfolio management. This paper proposes a novel LLM-guided no-regret portfolio allocation framework that integrates online learning dynamics, market sentiment indicators, and large language model (LLM)-based hedging to construct...

💬 0 commentsarXiv:2601.17021v1PDF
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Posted in q-bio.GN · 2026-01-16 · Shuai Yan, Qingzhi Yu, Wengfeng Dai, Xiang Cheng

GP-DHT: A Dual-Head Transformer with Contras-tive Learning for Predicting Gene Regulatory Rela-tionships across Species from Single-Cell Data

Gene regulatory networks (GRNs) are essential for understanding cell fate decisions and disease mechanisms, yet cross-species GRN inference from single-cell RNA-seq data remains challenging due to noise, sparsity, and cross-species distribution shifts. We propose GP-DHT (GenePair DualHeadTransformer), a cross-species single-cell GRN...

💬 0 commentsarXiv:2601.10995v1PDF
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Posted in stat.ME · 2026-01-16 · Xiaojing Sun, Bingxin Zhao, Fei Xue

Generalized Heterogeneous Functional Model with Applications to Large-scale Mobile Health Data

Physical activity is crucial for human health. With the increasing availability of large-scale mobile health data, strong associations have been found between physical activity and various diseases. However, accurately capturing this complex relationship is challenging, possibly because it varies across different subgroups of...

💬 0 commentsarXiv:2601.10994v1PDF
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Posted in stat.ML · 2026-01-16 · Minseo Kang, Seunghwan Park, Dongha Kim

Memorize Early, Then Query: Inlier-Memorization-Guided Active Outlier Detection

Outlier detection (OD) aims to identify abnormal instances, known as outliers or anomalies, by learning typical patterns of normal data, or inliers. Performing OD under an unsupervised regime-without any information about anomalous instances in the training data-is challenging. A recently observed phenomenon, known as the...

💬 0 commentsarXiv:2601.10993v2PDF
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Posted in cs.LG · 2026-01-16 · Kisung You

Constant Metric Scaling in Riemannian Computation

Constant rescaling of a Riemannian metric appears in many computational settings, often through a global scale parameter that is introduced either explicitly or implicitly. Although this operation is elementary, its consequences are not always made clear in practice and may be confused with changes in curvature, manifold structure, or...

💬 0 commentsarXiv:2601.10992v2PDF
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Posted in gr-qc · 2026-01-16 · Meghanil Sinha, Bharat Singh, S. Surendra Singh

Bose-Einstein condensate stars in massive gravity

This study explores the construction, validity and the properties of Boson or Bose-Einstein condensate (BEC) stars under the framework of de Rham-Gabadadze-Tolley (dRGT) like massive gravity, employing the Kuchowicz metric potential to model their internal structure. This gravitational framework accounts for a massive graviton while...

💬 0 commentsarXiv:2601.11673v1PDF
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Posted in cs.IT · 2026-01-16 · Hirosuke Yamamoto, Ken-ichi Iwata

Asymmetric Encoding-Decoding Schemes for Lossless Data Compression

This paper proposes a new lossless data compression coding scheme named an asymmetric encoding-decoding scheme (AEDS), which can be considered as a generalization of tANS (tabled variant of asymmetric numeral systems). In the AEDS, a data sequence $\mathbf{s}=s_1s_2\cdots s_n$ is encoded in backward order $s_t, t=n, \cdots, 2,1$,...

💬 0 commentsarXiv:2601.10991v1PDF
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Posted in cs.IR · 2026-01-16 · Ali Abedi, Charlene H. Chu, Shehroz S. Khan

Retrieval-Augmented Large Language Models for Evidence-Informed Guidance on Cannabidiol Use in Older Adults

Older adults commonly experience chronic conditions such as pain and sleep disturbances and may consider cannabidiol for symptom management. Safe use requires appropriate dosing, careful titration, and awareness of drug interactions, yet stigma and limited health literacy often limit understanding. Conversational artificial...

💬 0 commentsarXiv:2604.09548v1PDF
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Posted in math.OC · 2026-01-16 · Xinpo Li, Jingtao Shi

The Optimal Control Problem of Stochastic Differential System with Extended Mixed Delays and Applications

This paper investigates an optimal control problem where the system is described by a stochastic differential equation with extended mixed delays that contain point delay, extended distributed delay, and extended noisy memory. The model is general in that the extended mixed delays of the state variable and control variable are...

💬 0 commentsarXiv:2601.10990v1PDF
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Posted in astro-ph.GA · 2026-01-16 · Yancy L. Shirley, Jeffrey G. Mangum, Desika Narayanan, James Di Francesco

How To Use Thermal Dust Continuum Emission To Measure The Physical Properties Of Dusty Astrophysical Objects

Dust grains in the interstellar medium interact with photons across the electromagnetic spectrum. They are generally photon energy converters, absorbing short wavelength radiation and emitting long wavelength radiation. Sixty years ago in 1965, thermal emission from dust grains in the interstellar medium was discovered. This tutorial...

💬 0 commentsarXiv:2601.10989v1PDF
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Posted in cond-mat.mtrl-sci · 2026-01-16 · S. S. Das, M. Senthil Kumar

Enhancement of anomalous Hall effect in Si/Fe multilayers

Anomalous Hall effect studies were performed at 300 K on Si/Fe multilayers prepared by dc magnetron sputtering. About 60 times enhancement in the saturation Hall resistance and 80 times enhancement in anomalous Hall coefficient are obtained in [Si(50 angstrom)/Fe(tFe)]_20 multilayers when decreasing the Fe layer thickness from 100...

💬 0 commentsarXiv:2601.10988v1PDF
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Posted in cs.LG · 2026-01-16 · Aanand Balasubramanian, Sashank Silwal

Reasoning Distillation for Lightweight Automated Program Repair

We study whether lightweight symbolic reasoning supervision can improve fix type classification in compact automated program repair models. Small code models are attractive for resource-constrained settings, but they typically produce only a single prediction, making it unclear whether they learn meaningful program structure or rely...

💬 0 commentsarXiv:2601.10987v1PDF
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Posted in cs.CL · 2026-01-16 · R. James Cotton, Thomas Leonard

BiomechAgent: AI-Assisted Biomechanical Analysis Through Code-Generating Agents

Markerless motion capture is making quantitative movement analysis increasingly accessible, yet analyzing the resulting data remains a barrier for clinicians without programming expertise. We present BiomechAgent, a code-generating AI agent that enables biomechanical analysis through natural language and allows users to querying...

💬 0 commentsarXiv:2602.06975v1PDF
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Posted in cs.CL · 2026-01-16 · Bo Yang, Yunkui Chen, Lanfei Feng, Yu Zhang, Shijian Li

ZPD Detector: Data Selection via Capability-Difficulty Alignment for Large Language Models

As the cost of training large language models continues to increase and high-quality training data become increasingly scarce, selecting high-value samples or synthesizing effective training data under limited data budgets has emerged as a critical research problem. Most existing data selection methods rely on static criteria, such as...

💬 0 commentsarXiv:2601.10986v1PDF
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Posted in physics.optics · 2026-01-16 · Ieng-Wai Un, Subhajit Sarkar, Yonatan Sivan

Quantum-optical theory of the few femtosecond nonlinear optical response of Drude metals with a non-parabolic conduction band

We develop an energy-space density matrix framework to investigate the interaction of extremely short optical pulses (ESPs) with transparent conducting oxides (TCOs). This approach captures not only electron populations, material polarization, and the permittivity, but also the quantum coherences between states. Compared to...

💬 0 commentsarXiv:2601.10985v2PDF
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Posted in hep-ph · 2026-01-16 · Kamal Maayergi, Devin G. E. Walker, Ora Cullen, Michael E. Peskin

The Sensitivity of Higgs Factories to Composite Higgs Models via Precision Measurements

We investigate the potential of precision Higgs factory measurements to discover signatures of a representative model of electroweak symmetry breaking in which the Higgs boson arises as a composite Nambu-Goldstone boson. In this model, as in other models of the ``Little Higgs" or Natural Composite Higgs type, the primary perturbations...

💬 0 commentsarXiv:2601.10984v1PDF
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Posted in cs.CY · 2026-01-16 · Zhen Xu, Xin Guan, Chenxi Shi, Qinhao Chen, Renzhe Yu

Evaluating 21st-Century Competencies in Postsecondary Curricula with Large Language Models: Performance Benchmarking and Reasoning-Based Prompting Strategies

The growing emphasis on 21st-century competencies in postsecondary education, intensified by the transformative impact of generative AI, underscores the need to evaluate how these competencies are embedded in curricula and how effectively academic programs align with evolving workforce and societal demands. Curricular Analytics,...

💬 0 commentsarXiv:2601.10983v1PDF
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Posted in astro-ph.IM · 2026-01-16 · M. Deng, J. Wu

A Novel, Beam-based Formalism for Active Impedance of Phased Arrays

The active impedance is a fundamental parameter for characterizing the behavior of large, uniform phased array antennas. However, its conventional calculation via the mutual impedance matrix (or the scattering matrix) offers limited physical intuition and can be computationally intensive. This paper presents a novel derivation of the...

💬 0 commentsarXiv:2601.10982v2PDF
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Posted in math.NA · 2026-01-16 · Xiaoying Dai, Miao Hu, Shuwei Shen

A model order reduction based adaptive parareal method for time-dependent partial differential equations

In this paper, we propose a model order reduction based adaptive parareal method for time-dependent partial differential equations. By using the data obtained by the fine propagator in each iteration of the plain parareal method together with some model order reduction technique, we construct the coarse propagator adaptively in each...

💬 0 commentsarXiv:2601.10981v1PDF
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Posted in eess.SP · 2026-01-16 · Mengning Li, Wenye Wang

Uni-Fi: Integrated Multi-Task Wi-Fi Sensing

Wi-Fi sensing technology enables non-intrusive, continuous monitoring of user locations and activities, which supports diverse smart home applications. Since different sensing tasks exhibit contextual relationships, their integration can enhance individual module performance. However, integrating sensing tasks across different studies...

💬 0 commentsarXiv:2601.10980v2PDF
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Posted in quant-ph · 2026-01-16 · Si-Min Wang, Ming-Liang Hu, Heng Fan

Off-resonant preservation and generation of imaginarity in distributed scenarios

We study the nonlocal advantage of quantum imaginarity (NAQI) and distillable imaginarity of assistance (DIA), which treat imaginarity as a resource in distributed scenarios. For two qubits interacting with a lossy cavity, it is shown that both the NAQI and DIA can be well preserved for long times in the presence of large and...

💬 0 commentsarXiv:2601.10979v2PDF