Tijmen Blankevoort

19 papers · 2019–2025 · 7 conferences · across top CS/AI conferences

Achievements

+11 more ↓

🏃 Academic Marathon (6) 🌍 Conference Polyglot (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird

🧭 Keyword Pioneer 🌍 Conference Polyglot (7) 🏃 Academic Marathon (6) 🧬 Topic Evolution 👑 Triple Crown 🏆 Keyword Champion (3) 🗃️ Keyword Collector (59) ⚡ Prolific Year (6) 💎 Century Club (19) 🔥 Unstoppable (7) ❓ The Questioner (2)

Conferences

ICLR (6) NIPS (5) EMNLP (2) ICCV (2) ICML (2) CVPR (1) ECCV (1)

Top co-authors

Markus Nagel (9) Mart van Baalen (7) Max Welling (5) Christos Louizos (4) Babak Ehteshami Bejnordi (3) Yelysei Bondarenko (3) Andrey Kuzmin (2) Dawid Jan Kopiczko (2) Ying Wang (2) Yuki M Asano (2)

Keywords

model compression (7) neural network quantization (5) quantization-aware training (3) model quantization (3) post-training quantization (3) neural network pruning (2) attention mechanism (2) neural network (2) weight quantization (2) neural architecture search (1) batch normalization (1) knowledge distillation (1) catastrophic forgetting (1) bidirectional attention (1) bias correction (1) knowledge transfer (1) instruction tuning (1) neural network optimization (1) efficient inference (1) conditional computation (1)

Papers

Bitune: Leveraging Bidirectional Attention to Improve Decoder-Only LLMs EMNLP 2025 SpinQuant: LLM Quantization with Learned Rotations ICLR 2025 VeRA: Vector-based Random Matrix Adaptation ICLR 2024 The LLM Surgeon ICLR 2024 Scalarization for Multi-Task and Multi-Domain Learning at Scale NIPS 2023 Pruning vs Quantization: Which is Better? NIPS 2023 Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing NIPS 2023 FP8 Quantization: The Power of the Exponent NIPS 2022 Overcoming Oscillations in Quantization-Aware Training ICML 2022 Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces ICCV 2021 Understanding and Overcoming the Challenges of Efficient Transformer Quantization EMNLP 2021 Bayesian Bits: Unifying Quantization and Pruning NIPS 2020 Conditional Channel Gated Networks for Task-Aware Continual Learning CVPR 2020 Differentiable Joint Pruning and Quantization for Hardware Efficiency ECCV 2020 Gradient $\ell_1$ Regularization for Quantization Robustness ICLR 2020 Batch-shaping for learning conditional channel gated networks ICLR 2020 Up or Down? Adaptive Rounding for Post-Training Quantization ICML 2020 Data-Free Quantization Through Weight Equalization and Bias Correction ICCV 2019 Relaxed Quantization for Discretized Neural Networks ICLR 2019