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

PhySkin: Physics-based Bone-driven Neural Garment Simulation

Astitva Srivastava, Hsiao-yu Chen, Ryan Goldade, Philipp Herholz, Zhongshi Jiang, Gene Wei-Chin Lin, Lingchen Yang, Nikolaos Sarafianos, Tuur Stuyck, Egor Larionov ยท 2026

Recent advances in digital avatar technology have enabled the generation of compelling virtual characters, but deploying these avatars on compute-constrained devices poses significant challenges for aโ€ฆ

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The Observability Gap: Why Output-Level Human Feedback Fails for LLM Coding Agents

Yinghao Wang, Cheng Wang ยท 2026

Large language model (LLM) multi-agent coding systems typically fix agent capabilities at design time. We study an alternative setting, earned autonomy, in which a coding agent starts with zero pre-deโ€ฆ

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GAN-Enhanced Deep Reinforcement Learning for Semantic-Aware Resource Allocation in 6G Network Slicing

Daniel Benniah John ยท 2026

Sixth-generation (6G) wireless networks must support heterogeneous services: enhanced Mobile Broadband (eMBB) requiring 1 Tbps data rates, massive Machine-Type Communications (mMTC) supporting 10 millโ€ฆ

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Unlocking Open-Player-Modeling-enhanced Game-Based Learning: The Open Player Socially Analytical Intelligence Architecture

Zhiyu Lin, Boyd Fox, Devon Mckee, Sai Siddartha Maram, Jiahong Li, Tyler Sorensen, Brian K. Smith, Roger Azevedo, Jichen Zhu, Magy Seif El-Nasr ยท 2026

Game-Based Learning (GBL) is a learner-engaging pedagogical methodology, yet adapting games to heterogeneous learners requires transparent, real-time Open Player Models (OPMs). We contribute to the coโ€ฆ

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KI-Adventskalender: An Informal Learning Intervention for Data & AI Literacy

Rahul Sharma, Lars Henrich, Larisa Ivanova, Arsalan Karimzadmotallebiazar, Annette Bieniusa, Leo Van Waveren, Sebastian Vollmer ยท 2026

Secondary school students increasingly encounter AI systems whose outputs depend on data quality, evaluation choices and modeling assumptions. To provide accessible entry points to these interconnecteโ€ฆ

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Learning to Commit: Generating Organic Pull Requests via Online Repository Memory

Mo Li, L.H. Xu, Qitai Tan, Ting Cao, Yunxin Liu ยท 2026

Large language model (LLM)-based coding agents achieve impressive results on controlled benchmarks yet routinely produce pull requests that real maintainers reject. The root cause is not functional inโ€ฆ

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Machine Learning Transferability for Malware Detection

Cesar Vieira, Joao Vitorino, Eva Maia, Isabel Praca ยท 2026

Malware continues to be a predominant operational risk for organizations, especially when obfuscation techniques are used to evade detection. Despite the ongoing efforts in the development of Machine โ€ฆ

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Learning From Social Interactions: Personalized Pricing and Buyer Manipulation

Qinqi Lin, Lingjie Duan, Jianwei Huang ยท 2026

As the sociological theory of homophily suggests, people tend to interact with those of similar preferences. Motivated by this well-established phenomenon, today's online sellers, such as Amazon,~seekโ€ฆ

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EZASP -- Facilitating the usage of ASP

Rafael Martins, Matthias Knorr, Ricardo Goncalves ยท 2026

Answer Set Programming (ASP) is a declarative programming language used for modeling and solving complex combinatorial problems. It has been successfully applied to a number of different realworld proโ€ฆ

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CR-Eyes: A Computational Rational Model of Visual Sampling Behavior in Atari Games

Martin Lorenz, Niko Konzack, Alexander Lingler, Philipp Wintersberger, Patrick Ebel ยท 2026

Designing mobile and interactive technologies requires understanding how users sample dynamic environments to acquire information and make decisions under time pressure. However, existing computationaโ€ฆ

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Shaping Credibility Judgments in Human-GenAI Partnership via Weaker LLMs: A Transactive Memory Perspective on AI Literacy

Md Touhidul Islam, Mahir Akgun, Syed Billah ยท 2026

Generative AI (GenAI) is increasingly used as a knowledge partner in higher education, raising the need for instructional designs that emphasize AI literacy practices such as evaluating output credibiโ€ฆ

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Reentrancy Detection in the Age of LLMs

Dalila Ressi, Alvise Spano, Matteo Rizzo, Lorenzo Benetollo, Sabina Rossi ยท 2026

Reentrancy remains one of the most critical classes of vulnerabilities in Ethereum smart contracts, yet widely used detection tools and datasets continue to reflect outdated patterns and obsolete Soliโ€ฆ

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Fair Data Pre-Processing with Imperfect Attribute Space

Ying Zheng, Yangfan Jiang, Kian-Lee Tan ยท 2026

Fair data pre-processing is a widely used strategy for mitigating bias in machine learning. A promising line of research focuses on calibrating datasets to satisfy a designed fairness policy so that sโ€ฆ

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A Lightweight High-Throughput Collective-Capable NoC for Large-Scale ML Accelerators

Luca Colagrande, Lorenzo Leone, Chen Wu, Tim Fischer, Raphael Roth, Luca Benini ยท 2026

The exponential increase in Machine Learning (ML) model size and complexity has driven unprecedented demand for high-performance acceleration systems. As technology scaling enables the integration of โ€ฆ

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Towards Privacy-Preserving Federated Learning using Hybrid Homomorphic Encryption

Ivan Costa, Pedro Correia, Ivone Amorim, Eva Maia, Isabel Praca ยท 2026

Federated Learning (FL) enables collaborative training while keeping sensitive data on clients' devices, but local model updates can still leak private information. Hybrid Homomorphic Encryption (HHE)โ€ฆ

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Large Language Models for Software Testing Education: an Experience Report

Peng Yang, Yunfeng Zhu, Chao Chang, Shengcheng Yu, Zhenyu Chen, Yong Tang ยท 2026

The rapid integration of Large Language Models (LLMs) into software engineering practice is reshaping how software testing activities are performed. LLMs are increasingly used to support software testโ€ฆ

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Large language models for post-publication research evaluation: Evidence from expert recommendations and citation indicators

Mengjia Wu, Yi Zhang, Robin Haunschild, Lutz Bornmann ยท 2026

Assessing the quality of scientific research is essential for scholarly communication, yet widely used approaches face limitations in scalability, subjectivity, and time delay. Recent advances in largโ€ฆ

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Simulating Novice Students Using Machine Unlearning and Relearning in Large Language Models

Jiajia Song, Zhihan Guo, Jionghao Lin ยท 2026

Student simulation can support learning-by-teaching pedagogy where human students (as tutors) teach AI-simulated novice students (as tutees). Recent research often relies on prompt engineering with laโ€ฆ

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Rethinking Recommendation Paradigms: From Pipelines to Agentic Recommender Systems

Jinxin Hu, Hao Deng, Lingyu Mu, Hao Zhang, Shizhun Wang, Yu Zhang, Xiaoyi Zeng ยท 2026

Large-scale industrial recommenders typically use a fixed multi-stage pipeline (recall, ranking, re-ranking) and have progressed from collaborative filtering to deep and large pre-trained models. Howeโ€ฆ

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A Human-Inspired Decoupled Architecture for Efficient Audio Representation Learning

Harunori Kawano, Takeshi Sasaki ยท 2026

While self-supervised learning (SSL) has revolutionized audio representation, the excessive parameterization and quadratic computational cost of standard Transformers limit their deployment on resourcโ€ฆ

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