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๐Ÿ” avoidance learning ๐Ÿ“‚ Computer Science
Showing 46580 results for "avoidance learning" in Computer Science
Computer Science Preprint PDF DOI

DEEP-GAP: Deep-learning Evaluation of Execution Parallelism in GPU Architectural Performance

Kathiravan Palaniappan ยท 2026

Modern datacenters increasingly rely on low-power, single-slot inference accelerators to balance performance, energy efficiency, and rack density constraints. The NVIDIA T4 GPU has become widely deploโ€ฆ

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Bias in Surface Electromyography Features across a Demographically Diverse Cohort

Aditi Agrawal, Celine John Philip, Giancarlo K. Sagastume, Marcus A. Battraw, Wilsaan M. Joiner, Jonathon S. Schofield, Lee M. Miller, Richard S. Whittle ยท 2026

Neuromotor decoding from upper-limb electromyography (sEMG) can enhance human-machine interfaces and offer a more natural means of controlling prosthetic limbs, virtual reality, and household electronโ€ฆ

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Computer Science Preprint PDF DOI

NeuroTrace: Inference Provenance-Based Detection of Adversarial Examples

Firas Ben Hmida, Philemon Hailemariam, Kashif Ali Khan, Birhanu Eshete ยท 2026

Deep neural networks (DNNs) remain largely opaque at inference time, limiting our ability to detect and diagnose malicious input manipulations such as adversarial examples. Existing detection methods โ€ฆ

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Computer Science Preprint PDF DOI

CMOS-integrated superparamagnetic tunnel junction-based p-bit

Ju-Young Yoon, Nuno Cacoilo, Advait Madhavan, Jabez J. McClelland, Shun Kanai, Hideo Ohno, Shunsuke Fukami, William A. Borders ยท 2026

Probabilistic computers offer promising solutions for computationally hard problems in domains such as combinatorial optimization and machine learning. A key building block in these systems is the proโ€ฆ

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Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks

Fortunatus Aabangbio Wulnye, Justice Owusu Agyemang, Kwame Opuni-Boachie Obour Agyekum, Kwame Agyeman-Prempeh Agyekum, Kingsford Sarkodie Obeng Kwakye, Francisca Adomaa Acheampong ยท 2026

Ensuring the reliability of machine learning-based intrusion detection systems remains a critical challenge in Internet of Things (IoT) environments, particularly as data poisoning attacks increasinglโ€ฆ

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Computer Science Preprint PDF DOI

ToxiShield: Promoting Inclusive Developer Communication through Real-Time Toxicity Filtering

MD Awsaf Alam Anindya, Showvik Biswas, Anindya Iqbal, Jaydeb Sarker, Amiangshu Bosu ยท 2026

Toxic interactions during code reviews can undermine teamwork and hinder productivity in software engineering (SE) teams. While prior studies explore toxicity detection and empirical investigation, thโ€ฆ

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Digital Guardians: The Past and The Future of Cyber-Physical Resilience

Saurabh Bagchi, Hyunseung Kim, Tarek Abdelzaher, Homa Alemzadeh, Somali Chaterji, Glen Chou, Yuying Duan, Fanxin Kong, Michael Lemmon, Yin Li, Mengyu Liu, Wenhao Luo, Meiyi Ma, Sibin Mohan, Ayan Mukhopadhyay, Melkior Ornik, Dimitra Panagou, Kristin Yvonne Rozier, Ivan Ruchkin, Huajie Shao, Sze Zheng Yong, Majid Zamani, Xugui Zhou ยท 2026

Resilience in cyber-physical systems (CPS) is the fundamental ability to maintain safety and critical functionality despite adverse "perturbations," which includes security attacks, environmental disrโ€ฆ

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Aerial Multi-Functional RIS in Fluid Antennas-Aided Full-Duplex Networks: A Self-Optimized Hybrid Deep Reinforcement Learning Approach

Li-Hsiang Shen, Yu-Quan Zheng ยท 2026

To address high data traffic demands of sixth-generation (6G) networks, this paper proposes a novel architecture that integrates autonomous aerial vehicles (AAVs) and multi-functional reconfigurable iโ€ฆ

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ID and Graph View Contrastive Learning with Multi-View Attention Fusion for Sequential Recommendation

Xiaofan Zhou, Kyumin Lee ยท 2026

Sequential recommendation has become increasingly prominent in both academia and industry, particularly in e-commerce. The primary goal is to extract user preferences from historical interaction sequeโ€ฆ

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Enhancing Local Life Service Recommendation with Agentic Reasoning in Large Language Model

Shiteng Cao, Xiaochong Lan, Yuwei Du, Jie Feng, Yinxing Liu, Xinlei Shi, Yong Li ยท 2026

Local life service recommendation is distinct from general recommendation scenarios due to its strong living need-driven nature. Fundamentally, accurately identifying a user's immediate living need anโ€ฆ

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Block-Based Pathfinding: A Minecraft System for Visualizing Graph Algorithms

Luca-Stefan Pirvu, Bogdan-Alexandru Maciuca, Andrei-Ciprian Rabu, Adrian-Marius Dumitran ยท 2026

Graph theory is a cornerstone of Computer Science education, yet entry-level students often struggle to map abstract node-edge relationships to practical applications. This paper presents the design aโ€ฆ

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Towards Personalizing Secure Programming Education with LLM-Injected Vulnerabilities

Matthew Frazier, Kostadin Damevski ยท 2026

According to constructivist theory, students learn software security more effectively when examples are grounded in their own code. Generic examples often fail to connect with students' prior work, liโ€ฆ

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Departure Time Choice with Parametric Heterogeneity: Equilibrium and Instability

Hillel Bar-Gera, Stephen D. Boyles, Liron Ravner ยท 2026

Vickrey's classic single-bottleneck departure time choice equilibrium model exhibits instability under many plausible day-to-day learning dynamics. Such instability is not observed in reality -- does โ€ฆ

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Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go?

Reem Alfayez, Manal Binkhonain ยท 2026

Sentiment analysis in software engineering focuses on understanding emotions expressed in software artifacts. Previous research highlighted the limitations of applying general off-the-shelf sentiment โ€ฆ

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DUET: Joint Exploration of User Item Profiles in Recommendation System

Yue Chen, Yifei Sun, Lu Wang, Fangkai Yang, Pu Zhao, Minjie Hong, Yifei Dong, Minghua He, Nan Hu, Jianjin Zhang, Zhiwei Dai, Yuefeng Zhan, Weihao Han, Hao Sun, Qingwei Lin, Weiwei Deng, Feng Sun, Qi Zhang, Saravan Rajmohan, Dongmei Zhang ยท 2026

Traditional recommendation systems represent users and items as dense vectors and learn to align them in a shared latent space for relevance estimation. Recent LLM-based recommenders instead leverage โ€ฆ

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Zero-shot Evaluation of Deep Learning for Java Code Clone Detection

Thomas S. Heinze ยท 2026

Deep Learning (DL) is becoming more and more widespread in clone detection, motivated by achieving near-perfect performance for this task. In particular in case of semantic code clones, which share onโ€ฆ

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OffloadFS: Leveraging Disaggregated Storage for Computation Offloading

Sungho Moon, Daegyu Han, Hera Koo, Sangeun Chae, Duck-Ho Bae, Euiseong Seo, Beomseok Nam ยท 2026

Disaggregated storage systems improve resource utilization and enable independent scaling of storage and compute resources by separating storage resources from computing resources in data centers. NVMโ€ฆ

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Towards Fine-grained Temporal Perception: Post-Training Large Audio-Language Models with Audio-Side Time Prompt

Yanfeng Shi, Pengfei Cai, Jun Liu, Qing Gu, Nan Jiang, Lirong Dai, Ian McLoughlin, Yan Song ยท 2026

Large Audio-Language Models (LALMs) enable general audio understanding and demonstrate remarkable performance across various audio tasks. However, these models still face challenges in temporal percepโ€ฆ

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EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

Boxuan Jiang, Chenyun Dai, Can Han ยท 2026

Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. While synthetic data generation via Generative Adversโ€ฆ

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Scalable Design for RIS-Assisted Multi-User Downlink System Empowered by RSMA under Partial CSI

Yifan Fang, Bile Peng, Yingyang Chen, Qiang Li, Marwa Chafii, Eduard A. Jorswieck ยท 2026

In large-scale reconfigurable intelligent surface (RIS) communication systems, the precise acquisition of channel state information (CSI) is challenging. Consider a practical RIS configuration where oโ€ฆ

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