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

Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation

Chu Zhao, Enneng Yang, Jianzhe Zhao, Guibing Guo ยท 2026

Direct Preference Optimization (DPO) guides large language models (LLMs) to generate recommendations aligned with user historical behavior distributions by minimizing preference alignment loss. Howeveโ€ฆ

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Unveiling the Security Risks of Federated Learning in the Wild: From Research to Practice

Jiahao Chen, Zhiming Zhao, Yuwen Pu, Chunyi Zhou, Zhou Feng, Songze Li, Shouling Ji ยท 2026

Federated learning (FL) has attracted substantial attention in both academia and industry, yet its practical security posture remains poorly understood. In particular, a large body of poisoning researโ€ฆ

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immUNITY: Detecting and Mitigating Low Volume & Slow Attacks with Programmable Switches and SmartNICs

Cuidi Wei, Shaoyu Tu, Daiki Hata, Toru Hasegawa, Yuki Koizumi, K. K. Ramakrishnan, Junji Takemasa, Timothy Wood ยท 2026

Our analysis of recent Internet traces shows that up to 71% of flows contain suspicious behaviors indicative of low-volume network attacks such as port scans. However, distinguishing anomalous trafficโ€ฆ

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Towards Extended Reality Intelligence for Monitoring and Predicting Patient Readmission Risks

Martin Sanchez, Nick Tran, Vuthea Chheang ยท 2026

Hospital readmissions remain a challenge for healthcare systems, especially among patients with chronic conditions such as diabetes. Unplanned readmissions within 30 days are costly, strain hospital rโ€ฆ

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Epistemic Observability in Language Models

Tony Mason ยท 2026

We find that models report highest confidence precisely when they are fabricating. Across four model families (OLMo-3, Llama-3.1, Qwen3, Mistral), self-reported confidence inversely correlates with acโ€ฆ

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Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations

Yonas Kassa, James Bonacci, Ping Wang ยท 2026

The transformative potential of large language models (LLMs) in education, such as improving accessibility and personalized learning, is being eclipsed by significant challenges. These challenges stemโ€ฆ

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COmPOSER: Circuit Optimization of mm-wave/RF circuits with Performance-Oriented Synthesis for Efficient Realizations

Subhadip Ghosh, Surya Srikar Peri, Ramprasath S., Sosina A. Berhan, Endalk Y. Gebru, Ramesh Harjani, Sachin S. Sapatnekar ยท 2026

This work presents COmPOSER, an open-source, end-to-end framework for RF/mm-wave design automation that translates target specifications into optimized circuits with layouts. It unifies schematic syntโ€ฆ

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Fluid Antenna Networks Beyond Beamforming: An AI-Native Control Paradigm for 6G

Ian F. Akyildiz, Tugce Bilen ยท 2026

Fluid Antenna Systems (FAS) introduce a new degree of freedom for wireless networks by enabling the physical antenna position to adapt dynamically to changing radio conditions. While existing studies โ€ฆ

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RISE: Real-time Image Processing for Spectral Energy Detection and Localization

Chung-Hsuan Tung, Zhenzhou Qi, Tingjun Chen ยท 2026

Energy detection is widely used for spectrum sensing, but accurately localizing the time and frequency occupation of signals in real-time for efficient spectrum sharing remains challenging. To addressโ€ฆ

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Profiling learners' affective engagement: Emotion AI, intercultural pragmatics, and language learning

Robert Godwin-Jones ยท 2026

Learning another language can be a highly emotional process, typically characterized by numerous frustrations and triumphs, big and small. For most learners, language learning does not follow a linearโ€ฆ

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ALICE: A Multifaceted Evaluation Framework of Large Audio-Language Models' In-Context Learning Ability

Yen-Ting Piao, Jay Chiehen Liao, Wei-Tang Chien, Toshiki Ogimoto, Shang-Tse Chen, Yun-Nung Chen, Chun-Yi Lee, Shao-Yuan Lo ยท 2026

While Large Audio-Language Models (LALMs) have been shown to exhibit degraded instruction-following capabilities, their ability to infer task patterns from in-context examples under audio conditioningโ€ฆ

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Hawkeye: Reproducing GPU-Level Non-Determinism

Erez Badash, Dan Boneh, Ilan Komargodski, Megha Srivastava ยท 2026

We present Hawkeye, a system for analyzing and reproducing GPU-level arithmetic operations. Using our framework, anyone can re-execute on a CPU the exact matrix multiplication operations underlying a โ€ฆ

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Meta-Learning for Repeated Bayesian Persuasion

Ata Poyraz Turna, Asrin Efe Yorulmaz, Tamer Basar ยท 2026

Classical Bayesian persuasion studies how a sender influences receivers through carefully designed signaling policies within a single strategic interaction. In many real-world environments, such interโ€ฆ

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Improving Generalization on Cybersecurity Tasks with Multi-Modal Contrastive Learning

Jianan Huang, Rodolfo V. Valentim, Luca Vassio, Matteo Boffa, Marco Mellia, Idilio Drago, Dario Rossi ยท 2026

The use of ML in cybersecurity has long been impaired by generalization issues: Models that work well in controlled scenarios fail to maintain performance in production. The root cause often lies in Mโ€ฆ

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DGNNFlow: A Streaming Dataflow Architecture for Real-Time Edge-based Dynamic GNN Inference in HL-LHC Trigger Systems

Davendra Maharaj, Tu Pham, Peter Meiring, Kyungmin Park, Sena Durgut, Cong Hao, Matteo Cremonesi ยท 2026

Dynamic GNN inference has exhibited effectiveness in High Energy Physics (HEP) experiments at High Luminosity Large Hadron Collider (HL-LHC) due to strong capability to model complex particle interactโ€ฆ

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Demonstration of Adapt4Me: An Uncertainty-Aware Authoring Environment for Personalizing Automatic Speech Recognition to Non-normative Speech

Niclas Pokel, Yiming Zhao, Pehuen Moure, Yingqiang Gao, Roman Bohringer ยท 2026

Personalizing Automatic Speech Recognition (ASR) for non-normative speech remains challenging because data collection is labor-intensive and model training is technically complex. To address these limโ€ฆ

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Beyond Accuracy: Towards a Robust Evaluation Methodology for AI Systems for Language Education

James Edgell, Wm. Matthew Kennedy, Isaac Pattis, Ben Knight, Danielle Carvalho, Elizabeth Wonnacott ยท 2026

The rapid adoption of large language models in AI-powered language education has created an urgent need for evaluations that assess pedagogical effectiveness, particularly in language learning--one ofโ€ฆ

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From School AI Readiness to Student AI Literacy: A National Multilevel Mediation Analysis of Institutional Capacity and Teacher Capability

Xiu Guan, Mingmin Zheng, Dragan Gasevic, Wenxin Guo, Yingqun Liu, Xibin Han, Danijela Gasevic, Ruiling Ma, Qi Wu, Lixiang Yan ยท 2026

Artificial intelligence (AI) is increasingly embedded in vocational education systems, yet empirical evidence linking institutional AI readiness to student learning outcomes remains limited. This studโ€ฆ

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ReViSQL: Achieving Human-Level Text-to-SQL

Yuxuan Zhu, Tengjun Jin, Yoojin Choi, Daniel Kang ยท 2026

Translating natural language to SQL (Text-to-SQL) is a critical challenge in both database research and data analytics applications. Recent efforts have focused on enhancing SQL reasoning by developinโ€ฆ

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TAPAS: Efficient Two-Server Asymmetric Private Aggregation Beyond Prio(+)

Harish Karthikeyan, Antigoni Polychroniadou ยท 2026

Privacy-preserving aggregation is a cornerstone for AI systems that learn from distributed data without exposing individual records, especially in federated learning and telemetry. Existing two-serverโ€ฆ

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