Shengen Yan
Associate Professor
Works on heterogeneous computing, intelligent computing, and AI systems.
Shengen Yan's lab at Tsinghua works in AI Systems & Hardware. 23 papers since 2023, 18 at top venues, mostly NeurIPS and ICCV. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 78%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 3 papers2026 · T1 2 · collecting
- 12 papers2025 · T1 10
- 7 papers2024 · T1 5
- 1 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, ICCV, ICLR, ACM MM, CVPR
Research focuspaper titles that use each topic's words
- heterogeneous computing0 papers
- heterogeneous0 papers
- intelligent computing0 papers
- computing0 papers
- intelligent0 papers
Paper list
From DBLP.
20263 papers
- DATELATIAS: A General Architecture-Operator Model for Spatial Accelerators with Complex Topology and Memory Hierarchy (opens in a new tab)
- ICLR (T1)PM-KVQ: Progressive Mixed-precision KV Cache Quantization for Long-CoT LLMs (opens in a new tab)
- EuroSys (T1)STAlloc: Enhancing Memory Efficiency in Large-Scale Model Training with Spatio-Temporal Planning (opens in a new tab)
202512 papers
- WWW (T1)AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms (opens in a new tab)
- NeurIPS (T1)Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation (opens in a new tab)
- ICCV (T1)DiTFastAttnV2: Head-Wise Attention Compression for Multi-Modality Diffusion Transformers (opens in a new tab)
- ICCV (T1)Dlfr-Gen: Diffusion-Based Video Generation With Dynamic Latent Frame Rate (opens in a new tab)
- ACM MMDLFR-VAE: Dynamic Latent Frame Rate VAE for Video Generation (opens in a new tab)
- IEEE Trans. ComputersFlashDecoding++Next: High Throughput LLM Inference With Latency and Memory Optimization (opens in a new tab)
- ICCV (T1)FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models (opens in a new tab)
- ICLR (T1)Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better (opens in a new tab)
- CVPR (T1)MBQ: Modality-Balanced Quantization for Large Vision-Language Models (opens in a new tab)
- NeurIPS (T1)R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Token Routing (opens in a new tab)
- MLSys (T1)SOLA: Optimizing SLO Attainment for Large Language Model Serving with State-Aware Scheduling (opens in a new tab)
- ICLR (T1)ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation (opens in a new tab)
20247 papers
- DAC (T1)A Holistic Functionalization Approach to Optimizing Imperative Tensor Programs in Deep Learning (opens in a new tab)
- NeurIPS (T1)ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction (opens in a new tab)
- ENLSPCSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios (opens in a new tab)
- NeurIPS (T1)DiTFastAttn: Attention Compression for Diffusion Transformer Models (opens in a new tab)
- ICML (T1)Evaluating Quantized Large Language Models (opens in a new tab)
- ECCV (T1)MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization (opens in a new tab)
- IEEE Trans. Parallel Distributed Syst.Proteus: Simulating the Performance of Distributed DNN Training (opens in a new tab)
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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Data
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- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
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- Lab homepage
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