Beyond Labels: Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. - Lu Yin 006 (IJCAI, 2020)

Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing. - Lu Yin 006; Vlado Menkovski; Mykola Pechenizkiy (ECML/PKDD (2), 2020)

Hierarchical Semantic Segmentation using Psychometric Learning. - Lu Yin 006; Vlado Menkovski; Shiwei Liu 003; Mykola Pechenizkiy (ACML, 2021)

Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. - Shiwei Liu 003; Lu Yin 006; Decebal Constantin Mocanu; Mykola Pechenizkiy (ICML, 2021)

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. - Shiwei Liu 003; Tianlong Chen 001; Xiaohan Chen; Zahra Atashgahi; Lu Yin 006; Huanyu Kou; Li Shen 008; Mykola Pechenizkiy; Zhangyang Wang; Decebal Constantin Mocanu (NeurIPS, 2021)

Semantic-Based Few-Shot Learning by Interactive Psychometric Testing. - Lu Yin 006; Vlado Menkovski; Yulong Pei; Mykola Pechenizkiy (CoRR, 2021)

Semantic-Based Few-Shot Classification by Psychometric Learning. - Lu Yin 006; Vlado Menkovski; Yulong Pei; Mykola Pechenizkiy (IDA, 2022)

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. - Tianjin Huang; Tianlong Chen 001; Meng Fang; Vlado Menkovski; Jiaxu Zhao 002; Lu Yin 006; Yulong Pei; Decebal Constantin Mocanu; Zhangyang Wang; Mykola Pechenizkiy; Shiwei Liu 003 (LoG, 2022)

Superposing many tickets into one: A performance booster for sparse neural network training. - Lu Yin 006; Vlado Menkovski; Meng Fang; Tianjin Huang; Yulong Pei; Mykola Pechenizkiy (UAI, 2022)

Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. - Lu Yin 006; Vlado Menkovski; Meng Fang; Tianjin Huang; Yulong Pei; Mykola Pechenizkiy; Decebal Constantin Mocanu; Shiwei Liu 003 (CoRR, 2022)

Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. - Lu Yin 006; Shiwei Liu 003; Meng Fang; Tianjin Huang; Vlado Menkovski; Mykola Pechenizkiy (AAAI, 2023)

Are Large Kernels Better Teachers than Transformers for ConvNets? - Tianjin Huang; Lu Yin 006; Zhenyu Zhang 015; Li Shen 008; Meng Fang; Mykola Pechenizkiy; Zhangyang Wang; Shiwei Liu 003 (ICML, 2023)

Dynamic Sparsity Is Channel-Level Sparsity Learner. - Lu Yin 006; Gen Li 012; Meng Fang; Li Shen 008; Tianjin Huang; Zhangyang Wang; Vlado Menkovski; Xiaolong Ma; Mykola Pechenizkiy; Shiwei Liu 003 (NeurIPS, 2023)

Enhancing Adversarial Training via Reweighting Optimization Trajectory. - Tianjin Huang; Shiwei Liu 003; Tianlong Chen 001; Meng Fang; Li Shen 008; Vlado Menkovski; Lu Yin 006; Yulong Pei; Mykola Pechenizkiy (ECML/PKDD (1), 2023)

REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training. - Jiaxu Zhao 002; Lu Yin 006; Shiwei Liu 003; Meng Fang; Mykola Pechenizkiy (ECML/PKDD (2), 2023)

Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity. - Lu Yin 006; Shiwei Liu 003; Ajay Jaiswal; Souvik Kundu 009; Zhangyang Wang (CoRR, 2023)

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. - Lu Yin 006; You Wu 001; Zhenyu Zhang 015; Cheng-Yu Hsieh; Yaqing Wang 007; Yiling Jia; Mykola Pechenizkiy; Yi Liang; Zhangyang Wang; Shiwei Liu 003 (CoRR, 2023)

Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. - Zahra Atashgahi; Xuhao Zhang; Neil Kichler; Shiwei Liu 003; Lu Yin 006; Mykola Pechenizkiy; Raymond N. J. Veldhuis; Decebal Constantin Mocanu (Trans. Mach. Learn. Res., 2023)

Are Sparse Neural Networks Better Hard Sample Learners? - Qiao Xiao; Boqian Wu; Lu Yin 006; Christopher Neil Gadzinski; Tianjin Huang; Mykola Pechenizkiy; Decebal Constantin Mocanu (BMVC, 2024)

Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. - Abhinav Bandari; Lu Yin 006; Cheng-Yu Hsieh; Ajay Jaiswal; Tianlong Chen 001; Li Shen 008; Ranjay Krishna; Shiwei Liu 003 (EMNLP, 2024)

FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. - Ajay Jaiswal; Bodun Hu; Lu Yin 006; Yeonju Ro; Tianlong Chen 001; Shiwei Liu 003; Aditya Akella (EMNLP, 2024)

NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization. - Gen Li 012; Lu Yin 006; Jie Ji; Wei Niu 002; Minghai Qin; Bin Ren; Linke Guo; Shiwei Liu 003; Xiaolong Ma (ICLR, 2024)

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. - Lu Yin 006; Ajay Kumar Jaiswal; Shiwei Liu 003; Souvik Kundu 009; Zhangyang Wang (ICML, 2024)

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. - Lu Yin 006; You Wu 001; Zhenyu Zhang 015; Cheng-Yu Hsieh; Yaqing Wang 007; Yiling Jia; Gen Li 012; Ajay Kumar Jaiswal; Mykola Pechenizkiy; Yi Liang; Michael Bendersky; Zhangyang Wang; et al. (ICML, 2024)

Advancing Dynamic Sparse Training by Exploring Optimization Opportunities. - Jie Ji; Gen Li 012; Lu Yin 006; Minghai Qin; Geng Yuan; Linke Guo; Shiwei Liu 003; Xiaolong Ma (ICML, 2024)

A Structural-Clustering Based Active Learning for Graph Neural Networks. - Ricky Maulana Fajri; Yulong Pei; Lu Yin 006; Mykola Pechenizkiy (IDA (1), 2024)

MSRS: Training Multimodal Speech Recognition Models from Scratch with Sparse Mask Optimization. - Adriana Fernandez-Lopez; Honglie Chen; Pingchuan Ma 001; Lu Yin 006; Qiao Xiao; Stavros Petridis; Shiwei Liu 003; Maja Pantic (INTERSPEECH, 2024)

Dynamic Data Pruning for Automatic Speech Recognition. - Qiao Xiao; Pingchuan Ma 001; Adriana Fernandez-Lopez; Boqian Wu; Lu Yin 006; Stavros Petridis; Mykola Pechenizkiy; Maja Pantic; Decebal Constantin Mocanu; Shiwei Liu 003 (INTERSPEECH, 2024)

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. - Boqian Wu; Qiao Xiao; Shiwei Liu 003; Lu Yin 006; Mykola Pechenizkiy; Decebal Constantin Mocanu; Maurice van Keulen; Elena Mocanu (NeurIPS, 2024)

OwLore: Outlier-weighed Layerwise Sampled Low-Rank Projection for Memory-Efficient LLM Fine-tuning. - Pengxiang Li; Lu Yin 006; Xiaowei Gao; Shiwei Liu 003 (CoRR, 2024)

From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. - Ajay Jaiswal; Lu Yin 006; Zhenyu Zhang 015; Shiwei Liu 003; Jiawei Zhao; Yuandong Tian; Zhangyang Wang (CoRR, 2024)

Robust Active Learning (RoAL): Countering Dynamic Adversaries in Active Learning with Elastic Weight Consolidation. - Ricky Maulana Fajri; Yulong Pei; Lu Yin 006; Mykola Pechenizkiy (CoRR, 2024)

Multimodal Contrastive Learning of Urban Space Representations from POI Data. - Xinglei Wang; Tao Cheng 004; Stephen Law; Zichao Zeng; Lu Yin 006; Junyuan Liu (CoRR, 2024)

OWLed: Outlier-weighed Layerwise Pruning for Efficient Autonomous Driving Framework. - Jiaxi Li; Lu Yin 006; Xilu Wang 001 (CoRR, 2024)

Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning. - Mingyu Cao; Gen Li 012; Jie Ji; Jiaqi Zhang; Xiaolong Ma; Shiwei Liu 003; Lu Yin 006 (CoRR, 2024)

Aspect-Based Few-Shot Learning. - Tim van Engeland; Lu Yin 006; Vlado Menkovski (CoRR, 2024)

Outlier-weighed Layerwise Sampling for LLM Fine-tuning. - Pengxiang Li; Lu Yin 006; Xiaowei Gao; Shiwei Liu 003 (ACL (Findings), 2025)

Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. - Zhenyu Zhang 015; Ajay Kumar Jaiswal; Lu Yin 006; Shiwei Liu 003; Jiawei Zhao; Yuandong Tian; Zhangyang Wang (CPAL, 2025)

Full-Rank No More: Low-Rank Weight Training for Modern Speech Recognition Models. - Adriana Fernandez-Lopez; Shiwei Liu 003; Lu Yin 006; Stavros Petridis; Maja Pantic (ICASSP, 2025)

TODO: Enhancing LLM Alignment with Ternary Preferences. - Yuxiang Guo 004; Lu Yin 006; Bo Jiang 001; Jiaqi Zhang (ICLR, 2025)

SEBRA : Debiasing through Self-Guided Bias Ranking. - Adarsh Kappiyath; Abhra Chaudhuri; Ajay Kumar Jaiswal; Ziquan Liu; Yunpeng Li; Xiatian Zhu; Lu Yin 006 (ICLR, 2025)

Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN. - Pengxiang Li; Lu Yin 006; Shiwei Liu 003 (ICLR, 2025)

Multi-modal contrastive learning of urban space representations from POI data. - Xinglei Wang; Tao Cheng 004; Stephen Law; Zichao Zeng; Lu Yin 006; Junyuan Liu (Comput. Environ. Urban Syst., 2025)

The Curse of Depth in Large Language Models. - Wenfang Sun; Xinyuan Song; Pengxiang Li; Lu Yin 006; Yefeng Zheng 001; Shiwei Liu 003 (CoRR, 2025)

CLIMB-3D: Continual Learning for Imbalanced 3D Instance Segmentation. - Vishal Thengane; Jean Lahoud; Hisham Cholakkal; Rao Muhammad Anwer; Lu Yin 006; Xiatian Zhu; Salman Khan 001 (CoRR, 2025)

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling. - Bram Grooten; Farid Hasanov; Chenxiang Zhang; Qiao Xiao; Boqian Wu; Zahra Atashgahi; Ghada Sokar; Shiwei Liu 003; Lu Yin 006; Elena Mocanu; Mykola Pechenizkiy; Decebal Constantin Mocanu (CoRR, 2025)

Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution. - Qiao Xiao; Alan Ansell; Boqian Wu; Lu Yin 006; Mykola Pechenizkiy; Shiwei Liu 003; Decebal Constantin Mocanu (CoRR, 2025)

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning. - Zihang Liu; Tianyu Pang; Oleg Balabanov; Chaoqun Yang; Tianjin Huang; Lu Yin 006; Yaoqing Yang; Shiwei Liu 003 (CoRR, 2025)

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places. - Xinglei Wang; Tao Cheng 004; Stephen Law; Zichao Zeng; Ilya Ilyankou; Junyuan Liu; Lu Yin 006; Weiming Huang; Natchapon Jongwiriyanurak (CoRR, 2025)

AlphaDecay: Module-wise Weight Decay for Heavy-Tailed Balancing in LLMs. - Di He; Ajay Jaiswal; Songjun Tu; Li Shen 008; Ganzhao Yuan; Shiwei Liu 003; Lu Yin 006 (CoRR, 2025)

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching. - Guinan Su; Li Shen 008; Lu Yin 006; Shiwei Liu 003; Yanwu Yang; Jonas Geiping (CoRR, 2025)

Double-Checker: Enhancing Reasoning of Slow-Thinking LLMs via Self-Critical Fine-Tuning. - Xin Xu; Tianlong Chen 001; Fan Zhang; Wanlong Liu; Pengxiang Li; Ajay Kumar Jaiswal; Yuchen Yan; Jishan Hu; Yang Wang 020; Hao Chen; Shiwei Liu 003; Shizhe Diao; et al. (CoRR, 2025)

LOST: Low-rank and Sparse Pre-training for Large Language Models. - Jiaxi Li; Lu Yin 006; Li Shen 008; Jinjin Xu; Liwu Xu; Tianjin Huang; Wenwu Wang 001; Shiwei Liu 003; Xilu Wang 001 (CoRR, 2025)