Jianfei Chen
Associate Professor
Works on efficient deep learning algorithms, including quantized and memory-efficient training, and efficient algorithms for generative models.
Jianfei Chen's lab at Tsinghua works on generative & foundation models and efficient training & inference. 41 papers since 2023, 39 at top venues, mostly ICML and ICLR. 9 PhD students and 3 master's students. Applications close .
At a glance
- papers, 2023–2026
- 11/ year
- at T1 venues
- 95%
- PhD students
- 9
- MS students
- 3
- alumni listed
- 0
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 8 · collecting
- 18 papers2025 · T1 16
- 7 papers2024 · T1 7
- 8 papers2023 · T1 8
T1 venuesOtherVenues: ICML, ICLR, NeurIPS, AAAI, ACM MM
Research focuspaper titles that use each topic's words
- Efficient training & inference20 papers
- Generative & foundation models10 papers
- efficient8 papers
- algorithms0 papers
- efficient algorithms0 papers
Paper list
From the lab homepage.
20268 papers
- ICLR (T1)Achieving low-bit Muon through subspace preservation and grid quantization
- NeurIPS (T1)CSLA: Sparse-Linear Attention with Learnable Routing and Quantization-aware Training
- ICML (T1)Deterministic Differentiable Structured Pruning for Large Language Models
- ICML (T1)HexGen-3: A Fully Disaggregated LLM Serving Framework with Fine-Grained Heterogeneous Resource Autoscaling
- ICLR (T1)Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency
- ICLR (T1)SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse-Linear Attention
- ICML (T1)TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control
- NeurIPS (T1)Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
202518 papers
- NeurIPS (T1)Accelerating Video Diffusion Transformers with Sparse Attention via Semantic-Aware Permutation
- ICLR (T1)COAT: Compressing Optimizer states and Activations for Memory-Efficient FP8 Training
- ICLR (T1)Diffusion Bridge Implicit Models
- ICLR (T1)Elucidating the Preconditioning in Consistency Distillation
- ICML (T1)FrameBridge: Improving Image-to-Video Generation with Bridge Models
- ACM MMMaximum Redundancy Pruning: A Principle-Driven Layerwise Sparsity Allocation for LLMs
- ICLR (T1)On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
- ICML (T1)Oscillation-Reduced MXFP4 Training for Vision Transformers
- AAAI (T1)Pruning Large Language Models with Semi-Structural Adaptive Sparse Training
- ICLR (T1)ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing
- ICLR (T1)SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration
- ICML (T1)SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization
20247 papers
- ICML (T1)Accelerating Transformer Pre-training with 2:4 Sparsity
- NeurIPS (T1)C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory
- TMLR (T1)Calibrating Deep Ensemble through Functional Variational Inference
- NeurIPS (T1)Consistency Diffusion Bridge Models
- ICLR (T1)Efficient Backpropagation with Variance Controlled Adaptive Sampling
- ICML (T1)Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
- NeurIPS (T1)S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training
20238 papers
- ICML (T1)Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning
- NeurIPS (T1)DPM-Solver-v3: Improved Diffusion ODE Solvers with Empirical Model Statistics
- ICML (T1)Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
- NeurIPS (T1)Memory Efficient Optimizers with 4-bit States
- Nature Machine Intelligence (T1)Parameter-efficient fine-tuning of large-scale pre-trained language models
- ICLR (T1)Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models
- ICML (T1)Stabilizing GANs’ Training with Brownian Motion Controller
- NeurIPS (T1)Training Transformers with 4-bit Integers
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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