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Mykola Pechenizkiy

Eindhoven University of Technology, Netherlands

43 papers at tracked venues · 17 at CORE A* · active 2024–2026

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Venues

ECML-PKDD ×13ACL ×5ICLR ×4AAAI ×3AAMAS ×3EMNLP ×3ICML ×3ECAI ×2NeurIPS ×2AISTATS ×1BMVC ×1EACL ×1ICDM ×1InterSpeech ×1

Frequent coauthors

Jiaxu Zhao
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Mattia Cerrato
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Wenhan Han
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Yucheng Yang
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Qiao Xiao
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Inês Dutra
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Xin Du
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Boqian Wu
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Zahra Atashgahi
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Xiao Xiao
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Bernhard Pfahringer
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Shunfeng Zheng
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Papers

  1. Investigating Social Bias Propagation in Federated Fine-tuning of Large Language Models
    AAAI 2026 ·
    Jiaxu Zhao
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  2. MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in Indonesia
    EACL 2026 ·
    Xiao Xiao
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  3. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IX
    ECML-PKDD 2026 ·
    Inês Dutra
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  4. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track and Demo Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part X
    ECML-PKDD 2026 ·
    Inês Dutra
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  5. Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VIII
    ECML-PKDD 2026 ·
    Bernhard Pfahringer
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  6. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Revised Selected Papers, Part I
    ECML-PKDD 2026 ·
    Mattia Cerrato
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  7. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Revised Selected Papers, Part II
    ECML-PKDD 2026 ·
    Mattia Cerrato
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  8. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Revised Selected Papers, Part III
    ECML-PKDD 2026 ·
    Mattia Cerrato
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  9. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Revised Selected Papers, Part IV
    ECML-PKDD 2026 ·
    Mattia Cerrato
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  10. MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages
    ACL 2026 ·
    Wenhan Han
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  11. mPresenter: An Agentic Framework for Generating Multilingual Presentation Videos from Scientific Papers
    ACL 2026 ·
    Wenhan Han
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  12. Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving
    EMNLP 2025 ·
    Shunfeng Zheng
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  13. Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles
    ICDM 2025 ·
    Xin Du
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  14. Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity
    AAMAS 2025 ·
    Calarina Muslimani
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  15. Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well
    ECML-PKDD 2025 ·
    Xin Du
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  16. Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
    ICLR 2025 ·
    Boqian Wu
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  17. From Benchmarking to Understanding FairML
    ECAI 2025 · Mykola Pechenizkiy
  18. HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents
    ICLR 2025 ·
    Tristan Tomilin
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  19. Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization
    ICML 2025 ·
    Yucheng Yang
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  20. REOBench: Benchmarking Robustness of Earth Observation Foundation Models
    NeurIPS 2025 ·
    Xiang Li
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  21. RuAG: Learned-rule-augmented Generation for Large Language Models
    ICLR 2025 ·
    Yudi Zhang
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  22. Understanding Large Language Model Vulnerabilities to Social Bias Attacks
    ACL 2025 ·
    Jiaxu Zhao
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  23. Unmasking Style Sensitivity: A Causal Analysis of Bias Evaluation Instability in Large Language Models
    ACL 2025 ·
    Jiaxu Zhao
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  24. Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective
    AAAI 2025 ·
    Can Jin
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  25. Achieving Long-Term Time Series Forecasting Models with Fewer Than 1k Parameters Through Dynamic Sparse Training
    ECML-PKDD 2024 ·
    Qiao Xiao
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  26. Adaptive Sparsity Level During Training for Efficient Time Series Forecasting with Transformers
    ECML-PKDD 2024 ·
    Zahra Atashgahi
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  27. Are Sparse Neural Networks Better Hard Sample Learners?
    BMVC 2024 ·
    Qiao Xiao
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  28. Automatic Curriculum for Unsupervised Reinforcement Learning
    AAMAS 2024 ·
    Yucheng Yang
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  29. CHAmbi: A New Benchmark on Chinese Ambiguity Challenges for Large Language Models
    EMNLP 2024 ·
    Qin Zhang
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  30. Dynamic Data Pruning for Automatic Speech Recognition
    InterSpeech 2024 ·
    Qiao Xiao
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  31. E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation
    NeurIPS 2024 ·
    Boqian Wu
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  32. Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
    ICML 2024 ·
    Danil Provodin
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  33. Everyone Deserves their Voice to Be Heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data
    ECML-PKDD 2024 ·
    Rik Raes
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  34. Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression
    ECML-PKDD 2024 ·
    Rianne Margaretha Schouten
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  35. Large Language Models Are Neurosymbolic Reasoners
    AAAI 2024 ·
    Meng Fang
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  36. MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning
    AAMAS 2024 ·
    Bram Grooten
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  37. MedINST: Meta Dataset of Biomedical Instructions
    EMNLP 2024 ·
    Wenhan Han
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  38. More than Minorities and Majorities: Understanding Multilateral Bias in Language Generation
    ACL 2024 ·
    Jiaxu Zhao
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  39. Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity
    ICML 2024 ·
    Lu Yin
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  40. Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias
    ECML-PKDD 2024 ·
    Adam Dubowski
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  41. Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks
    AISTATS 2024 ·
    Kaiting Liu
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  42. Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
    ICLR 2024 ·
    Yucheng Yang
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  43. Unveiling the Power of Sparse Neural Networks for Feature Selection
    ECAI 2024 ·
    Zahra Atashgahi
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