conftrace_
← Authors

Mykola Pechenizkiy

43 papers · 2018–2026 · 13 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+13 more ↓ 🌍 Conference Polyglot (12) πŸƒ Academic Marathon (7) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (8)
🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (11) πŸ—ΊοΈ Taxonomy Completionist (84) 🧬 Topic Evolution 🀝 Dynamic Duo (21) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam ⚑ Prolific Year (7) πŸ’Ž Century Club (41) πŸ”₯ Unstoppable (6) ❓ The Questioner (3) πŸ—ƒοΈ Keyword Collector (152)

Conferences

ICLR (7) NIPS (7) ICML (6) AAAI (5) ACL (5) EMNLP (4) ACML (2) IJCAI (2) AISTATS (1) EACL (1) INTERSPEECH (1) NAACL (1) UAI (1)

Top co-authors

Meng Fang (23) Shiwei Liu (14) Decebal Constantin Mocanu (13) Lu Yin (10) Vlado Menkovski (7) Zhangyang Wang (6) Jiaxu Zhao (6) Ling Chen (6) Tianjin Huang (6) Yulong Pei (6)

Research topics

Applications (1)

Keywords

dynamic sparse training (5) model compression (5) neural network pruning (4) large language model (4) social bia (4) bias evaluation (3) sparse neural network (3) dynamic sparsity (2) gender bia (2) causal inference (2) debiasing method (2) sparse training (2) bias mitigation (2) feature selection (2) neural network sparsification (2) language model (2) convolutional neural network (2) benchmark dataset (2) sample efficiency (1) semantic segmentation (1)

Papers

MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in Indonesia EACL 2026 Investigating Social Bias Propagation in Federated Fine-tuning of Large Language Models AAAI 2026 RuAG: Learned-rule-augmented Generation for Large Language Models ICLR 2025 Unmasking Style Sensitivity: A Causal Analysis of Bias Evaluation Instability in Large Language Models ACL 2025 Understanding Large Language Model Vulnerabilities to Social Bias Attacks ACL 2025 Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization ICML 2025 Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness ICLR 2025 Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective AAAI 2025 HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents ICLR 2025 Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving EMNLP 2025 Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling ICML 2024 CHAmbi: A New Benchmark on Chinese Ambiguity Challenges for Large Language Models EMNLP 2024 Dynamic Data Pruning for Automatic Speech Recognition INTERSPEECH 2024 Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning ICLR 2024 Large Language Models Are Neurosymbolic Reasoners AAAI 2024 E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation NIPS 2024 More than Minorities and Majorities: Understanding Multilateral Bias in Language Generation ACL 2024 Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity ICML 2024 Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks AISTATS 2024 MedINST: Meta Dataset of Biomedical Instructions EMNLP 2024 Are Large Kernels Better Teachers than Transformers for ConvNets? ICML 2023 Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach NIPS 2023 COOM: A Game Benchmark for Continual Reinforcement Learning NIPS 2023 Dynamic Sparsity Is Channel-Level Sparsity Learner NIPS 2023 Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost AAAI 2023 NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist ACL 2023 CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models ACL 2023 More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity ICLR 2023 Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity ICLR 2022 The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training ICLR 2022 Dynamic Sparse Training for Deep Reinforcement Learning IJCAI 2022 Phrase-level Textual Adversarial Attack with Label Preservation NAACL 2022 Superposing many tickets into one: A performance booster for sparse neural network training UAI 2022 Dynamic Sparse Network for Time Series Classification: Learning What to β€œSee” NIPS 2022 Where to Pay Attention in Sparse Training for Feature Selection? NIPS 2022 Hierarchical Semantic Segmentation using Psychometric Learning ACML 2021 ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection EMNLP 2021 calibrated adversarial training ACML 2021 Selfish Sparse RNN Training ICML 2021 Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training ICML 2021 Sparse Training via Boosting Pruning Plasticity with Neuroregeneration NIPS 2021 Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data AAAI 2020 DyNMF: Role Analytics in Dynamic Social Networks IJCAI 2018