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

EvoSchema: Towards Text-to-SQL Robustness Against Schema Evolution

Tianshu Zhang, Kun Qian, Siddhartha Sahai, Yuan Tian, Shaddy Garg, Huan Sun, Yunyao Li ยท 2026

Neural text-to-SQL models, which translate natural language questions (NLQs) into SQL queries given a database schema, have achieved remarkable performance. However, database schemas frequently evolveโ€ฆ

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Computer Science Preprint PDF DOI

Repurposing Backdoors for Good: Ephemeral Intrinsic Proofs for Verifiable Aggregation in Cross-silo Federated Learning

Xian Qin, Xue Yang, Xiaohu Tang ยท 2026

While Secure Aggregation (SA) protects update confidentiality in Cross-silo Federated Learning, it fails to guarantee aggregation integrity, allowing malicious servers to silently omit or tamper with โ€ฆ

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Computer Science Preprint PDF DOI

Detecting and Eliminating Neural Network Backdoors Through Active Paths with Application to Intrusion Detection

Eirik H{o}yheim, Magnus Wiik Eckhoff, Gudmund Grov, Robert Flood, David Aspinall ยท 2026

Machine learning backdoors have the property that the machine learning model should work as expected on normal inputs, but when the input contains a specific $\textit{trigger}$, it behaves as the attaโ€ฆ

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Computer Science Preprint PDF DOI

QuantumX: an experience for the consolidation of Quantum Computing and Quantum Software Engineering as an emerging discipline

Juan M. Murillo, Ignacio Garcia Rodriguez de Guzman, Enrique Moguel, Javier Romero-Alvarez, Jaime Alvarado-Valiente, Alvaro M. Aparicio-Morales, Jose Garcia-Alonso, Ana Diaz Munoz, Eduardo Fernandez-Medina, Francisco Chicano, Carlos Canal, Jose Daniel Viqueira, Sebastian Villarroya, Eduardo Gutierrez, Adrian Romero-Flores, Alfonso E. Marquez-Chamorro, Antonio Ruiz-Cortes, Cyrille YetuYetu Kesiku, Pedro Sanchez, Diego Alonso Caceres, Lidia Sanchez-Gonzalez, Fernando Plou ยท 2026

The first edition of the QuantumX track, held within the XXIX Jornadas de Ingenier\'ia del Software y Bases de Datos (JISBD 2025), brought together leading Spanish research groups working at the interโ€ฆ

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Computer Science Preprint PDF DOI

TopGen: Learning Structural Layouts and Cross-Fields for Quadrilateral Mesh Generation

Yuguang Chen, Xinhai Liu, Xiangyu Zhu, Yiling Zhu, Zhuo Chen, Dongyu Zhang, Chunchao Guo ยท 2026

High-quality quadrilateral mesh generation is a fundamental challenge in computer graphics. Traditional optimization-based methods are often constrained by the topological quality of input meshes and โ€ฆ

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Computer Science Preprint PDF DOI

Draft-Refine-Optimize: Self-Evolved Learning for Natural Language to MongoDB Query Generation

Mingwei Ye, Jiaxi Zhuang, Mingjun Xu, Linfeng Zhang, Guolin Ke, Hengxing Cai ยท 2026

Natural Language to MongoDB Query Language (NL2MQL) is essential for democratizing access to modern document-centric databases. Unlike Text-to-SQL, NL2MQL faces unique challenges from MQL's proceduralโ€ฆ

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Computer Science Preprint PDF DOI

Beyond Single-Score Ranking: Facet-Aware Reranking for Controllable Diversity in Paper Recommendation

Duan Ming Tao ยท 2026

Current paper recommendation systems output a single similarity score that mixes different notions of relatedness, so users cannot specify why papers should be similar. We present SciFACE (Scientific โ€ฆ

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V2A-DPO: Omni-Preference Optimization for Video-to-Audio Generation

Nolan Chan, Timmy Gang, Yongqian Wang, Yuzhe Liang, Dingdong Wang ยท 2026

This paper introduces V2A-DPO, a novel Direct Preference Optimization (DPO) framework tailored for flow-based video-to-audio generation (V2A) models, incorporating key adaptations to effectively alignโ€ฆ

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Computer Science Preprint PDF DOI

Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks

Nasim Soltani, Shayan Nejadshamsi, Zakaria Abou El Houda, Raphael Khoury, Kelton A. P. Costa, Tiago H. Falk, Anderson R. Avila ยท 2026

Adversarial examples can represent a serious threat to machine learning (ML) algorithms. If used to manipulate the behaviour of ML-based Network Intrusion Detection Systems (NIDS), they can jeopardizeโ€ฆ

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WME: Extending CDCL-based Model Enumeration with Weights

Giuseppe Spallitta, Moshe Y. Vardi ยท 2026

In this work we investigate Weighted Model Enumeration (WME): given a Boolean formula and a weight function over its satisfying assignments, enumerate models while accounting for their weights. This sโ€ฆ

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Unifying Logical and Physical Layout Representations via Heterogeneous Graphs for Circuit Congestion Prediction

Runbang Hu, Bo Fang, Bingzhe Li, Yuede Ji ยท 2026

As Very Large Scale Integration (VLSI) designs continue to scale in size and complexity, layout verification has become a central challenge in modern Electronic Design Automation (EDA) workflows. In pโ€ฆ

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Multilingual AI-Driven Password Strength Estimation with Similarity-Based Detection

Nikitha M. Palaniappan, Ying He ยท 2026

Considering the rise of cyberattacks incidents worldwide, the need to ensure stronger passwords is necessary. Developing a password strength meter (PSM) can help users create stronger passwords when cโ€ฆ

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Context Before Code: An Experience Report on Vibe Coding in Practice

Md Nasir Uddin Shuvo, Md Aidul Islam, Md Mahade Hasan, Muhammad Waseem, Pekka Abrahamsson ยท 2026

Code-generating tools are increasingly used in software development, yet experience reports on conversational "vibe coding" under production constraints remain limited. This paper presents an experienโ€ฆ

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Learning to Decode Quantum LDPC Codes Via Belief Propagation

Mohsen Moradi, Vahid Nourozi, Salman Habib, David G. M. Mitchell ยท 2026

Belief-propagation (BP) decoding for quantum low-density parity-check (QLDPC) codes is appealing due to its low complexity, yet it often exhibits convergence issues due to quantum degeneracy and shortโ€ฆ

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Noncooperative Human-AI Agent Dynamics

Dylan Waldner, Vyacheslav Kungurtsev, Mitchelle Ashimosi ยท 2026

This paper investigates the dynamics of noncooperative interactions between artificial intelligence agents and human decision-makers in strategic environments. In particular, motivated by extensive liโ€ฆ

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Tetris is Hard with Just One Piece Type

MIT Hardness Group: Josh Brunner, Erik D. Demaine, Della Hendrickson, Jeffery Li ยท 2026

We analyze the computational complexity of Tetris clearing (determining whether the player can clear an initial board using a given sequence of pieces) and survival (determining whether the player canโ€ฆ

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Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models

Daniel Hennes, Zun Li, John Schultz, Marc Lanctot ยท 2026

Recent advances in multi-agent reinforcement learning, particularly Policy-Space Response Oracles (PSRO), have enabled the computation of approximate game-theoretic equilibria in increasingly complex โ€ฆ

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RecThinker: An Agentic Framework for Tool-Augmented Reasoning in Recommendation

Haobo Zhang, Yutao Zhu, Kelong Mao, Tianhao Li, Zhicheng Dou ยท 2026

Large Language Models (LLMs) have revolutionized recommendation agents by providing superior reasoning and flexible decision-making capabilities. However, existing methods mainly follow a passive infoโ€ฆ

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Classifying Problem and Solution Framing in Congressional Social Media

Misha Melnyk, Mitchell Dolny, Joshua D. Elkind, A. Michael Tjhin, Saisha Chebium, Blake VanBerlo, Annelise Russell, Michelle M. Buehlmann, Jesse Hoey ยท 2026

Policy setting in the USA according to the ``Garbage Can'' model differentiates between ``problem'' and ``solution'' focused processes. In this paper, we study a large dataset of US Senator postings oโ€ฆ

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Detecting Miscitation on the Scholarly Web through LLM-Augmented Text-Rich Graph Learning

Huidong Wu, Haojia Xiang, Jingtong Gao, Xiangyu Zhao, Dengsheng Wu, Jianping Li ยท 2026

Scholarly web is a vast network of knowledge connected by citations. However, this system is increasingly compromised by miscitation, where references do not support or even contradict the claims theyโ€ฆ

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