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

Optimal Exploration of New Products under Assortment Decisions

Jackie Baek, Atanas Dinev, Thodoris Lykouris ยท 2026

We study online learning for new products on a platform that makes capacity-constrained assortment decisions on which products to offer. For a newly listed product, its quality is initially unknown, aโ€ฆ

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From Business Problems to AI Solutions: Where Does Transformation Support Fail

Abir Trabelsi, Imen Benzarti, Hafedh Mili, Darine Ameyed ยท 2026

Translating business problems into well-specified machine learning solutions is a prerequisite for successful AI systems, yet this upstream translation is still one of the least supported steps in exiโ€ฆ

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Students Know AI Should Not Replace Thinking, but How Do They Regulate It? The TACO Framework for Human-AI Cognitive Partnership

Cecilia Ka Yuk Chan ยท 2026

As generative artificial intelligence becomes increasingly embedded in educational practice, a central concern is whether students use AI as cognitive support or as a substitute for thinking. Prior reโ€ฆ

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TrEEStealer: Stealing Decision Trees via Enclave Side Channels

Jonas Sander, Anja Rabich, Nick Mahling, Felix Maurer, Jonah Heller, Qifan Wang, Thomas Eisenbarth, David Oswald ยท 2026

Today, machine learning is widely applied in sensitive, security-related, and financially lucrative applications. Model extraction attacks undermine current business models where a model owner sells mโ€ฆ

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Fast and Forgettable: A Controlled Study of Novices' Performance, Learning, Workload, and Emotion in AI-Assisted and Human Pair Programming Paradigms

Nicholas Gardella, James Prather, Juho Leinonen, Paul Denny, Raymond Pettit, Sara L. Riggs ยท 2026

Code-generating Artificial Intelligence has gained popularity within both professional and educational programming settings over the past several years. While research and pedagogy are beginning to coโ€ฆ

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Computer Science Preprint PDF DOI

Different Paths to Harmful Compliance: Behavioral Side Effects and Mechanistic Divergence Across LLM Jailbreaks

Md Rysul Kabir, Zoran Tiganj ยท 2026

Open-weight language models can be rendered unsafe through several distinct interventions, but the resulting models may differ substantially in capabilities, behavioral profile, and internal failure mโ€ฆ

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Capturing Monetarily Exploitable Vulnerability in Smart Contracts via Auditor Knowledge-Learning Fuzzing

Bowen Cai, Weiheng Bai, Hangyun Tang, Youshui Lu, Kangjie Lu ยท 2026

Smart contracts extended blockchain functionality beyond simple transactions, powering complex applications like decentralized finance (DeFi). However, this complexity introduces serious security chalโ€ฆ

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OpenGame: Open Agentic Coding for Games

Yilei Jiang, Jinyuan Hu, Qianyin Xiao, Yaozhi Zheng, Ruize Ma, Kaituo Feng, Jiaming Han, Tianshuo Peng, Kaixuan Fan, Manyuan Zhang, Xiangyu Yue ยท 2026

Game development sits at the intersection of creative design and intricate software engineering, demanding the joint orchestration of game engines, real-time loops, and tightly coupled state across maโ€ฆ

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Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems

Runhao Jiang, Renchi Yang, Donghao Wu ยท 2026

Recommender systems have advanced markedly over the past decade by transforming each user/item into a dense embedding vector with deep learning models. At industrial scale, embedding tables constituteโ€ฆ

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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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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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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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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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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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Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining

Francesco Vitale, Francesco Grimaldi, Massimiliano Rak, Nicola Mazzocca ยท 2026

Anomaly-based Intrusion Detection Systems (IDSs) ensure protection against malicious attacks on networked systems. While deep learning-based IDSs achieve effective performance, their limited trustwortโ€ฆ

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ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks

Saeid Sheikhi, Panos Kostakos, Lauri Loven ยท 2026

Intrusion detection systems (IDSs) for 5G networks must handle complex, high-volume traffic. Although opaque "black-box" models can achieve high accuracy, their lack of transparency hinders trust and โ€ฆ

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HolmeSketcher: Generative 3D Sketch Mapping for Spatial Reconstruction in Crime Scene Investigation

Tianyi Xiao, Yizi Chen, Sidi Wu, Peter Kiefer, Yan Feng, Martin Raubal ยท 2026

Sketch mapping is widely used in crime scene investigation (CSI) to document, interpret, and communicate spatial information. However, it is typically performed on 2D media, which limits its ability tโ€ฆ

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CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora

Shangyu Li, Juyong Jiang, Meibo Ren, Sizhe Zhong, Huiri Tan, Yunhao Gou, Xu Han, Chun Yong Chong, Yun Peng, Jiasi Shen ยท 2026

Transpilation, or code translation, aims to convert source code from one programming language (PL) to another. It is beneficial for many downstream applications, from modernizing large legacy codebaseโ€ฆ

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Bayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval

Junyoung Kim, Anton Korikov, Jiazhou Liang, Justin Cui, Yifan Simon Liu, Qianfeng Wen, Mark Zhao, Scott Sanner ยท 2026

While Large Language Models (LLMs) exhibit exceptional zero-shot relevance modeling, their high computational cost necessitates framing passage retrieval as a budget-constrained global optimization prโ€ฆ

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Empowering Vocabulary Learning Through Teaching AI: Using LLMs as a Student to Perform Learning by Teaching in Vocabulary Acquisition

Tokio Uchida, Ko Watanabe, Andrew Vargo, Shoya Ishimaru, Ralph L. Rose, Ayaka Sugawara, Andreas Dengel, Koichi Kise ยท 2026

"Learning by Teaching (LbT)" helps learners deepen their understanding by explaining concepts to others, with questions playing a vital role in identifying knowledge gaps and reinforcing comprehensionโ€ฆ

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