← Authors

Yehui Tang

56 papers · 2020–2026 · 9 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (67) 🐝 Cross-Pollinator (7) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (5) 🀝 Dynamic Duo (40) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (54) πŸ—ƒοΈ Keyword Collector (168) ⚑ Prolific Year (16)

Conferences

CVPR (13) ICML (13) NIPS (12) AAAI (6) ECCV (4) ICLR (4) NAACL (2) ICCV (1) IJCAI (1)

Top co-authors

Yunhe Wang (41) Kai Han (29) Chang Xu (20) Chao Xu (15) Jianyuan Guo (11) Xinghao Chen (9) Junchi Yan (8) Yixing Xu (7) Chunjing XU (6) Zhiwei Hao (5)

Keywords

model compression (11) vision transformer (6) neural architecture search (4) image classification (4) knowledge distillation (4) convolutional neural network (3) domain adaptation (3) object detection (3) model architecture (3) large language model (3) filter pruning (2) efficient computing (2) edge computing (2) frequency domain (2) semantic segmentation (2) inference acceleration (2) network pruning (2) quantum computing (2) representation learning (2) neural network optimization (2)

Papers

PocketLLM: Ultimate Compression of Large Language Models via Meta Networks AAAI 2026
GenVidBench: A 6-Million Benchmark for AI-Generated Video Detection AAAI 2026
QuaDiM: A Conditional Diffusion Model For Quantum State Property Estimation ICLR 2025
CBQ: Cross-Block Quantization for Large Language Models ICLR 2025
DenseSSM: State Space Models with Dense Hidden Connection for Efficient Large Language Models NAACL 2025
Tensor Network: from the Perspective of AI4Science and Science4AI IJCAI 2025
LLM Data Selection and Utilization via Dynamic Bi-level Optimization ICML 2025
Mixture of Lookup Experts ICML 2025
SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs ICML 2025
EMS-SD: Efficient Multi-sample Speculative Decoding for Accelerating Large Language Models NAACL 2025
SlimLLM: Accurate Structured Pruning for Large Language Models ICML 2025
Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning ICML 2025
TinySAM: Pushing the Envelope for Efficient Segment Anything Model AAAI 2025
Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts AAAI 2025
QEM-Bench: Benchmarking Learning-based Quantum Error Mitigation and QEMFormer as a Multi-ranged Context Learning Baseline ICML 2025
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark ICLR 2024
Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning NIPS 2024
Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exiting NIPS 2024
MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers NIPS 2024
Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning CVPR 2024
Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuning ECCV 2024
Visual Prompting via Partial Optimal Transport ECCV 2024
Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation ECCV 2024
Adapt without Forgetting: Distill Proximity from Dual Teachers in Vision-Language Models ECCV 2024
Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space ICLR 2024
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization ICML 2024
Data-efficient Large Vision Models through Sequential Autoregression ICML 2024
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning ICML 2024
ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking ICML 2024
Rethinking Optimization and Architecture for Tiny Language Models ICML 2024
SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification ICML 2024
One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation NIPS 2023
Network Expansion for Practical Training Acceleration CVPR 2023
Masked Image Modeling With Local Multi-Scale Reconstruction CVPR 2023
Patch Slimming for Efficient Vision Transformers CVPR 2022
GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NIPS 2022
Hire-MLP: Vision MLP via Hierarchical Rearrangement CVPR 2022
Source-Free Domain Adaptation via Distribution Estimation CVPR 2022
An Image Patch Is a Wave: Phase-Aware Vision MLP CVPR 2022
CMT: Convolutional Neural Networks Meet Vision Transformers CVPR 2022
Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor NIPS 2022
Spatial-Channel Token Distillation for Vision MLPs ICML 2022
GhostNetV2: Enhance Cheap Operation with Long-Range Attention NIPS 2022
Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation NIPS 2022
Vision GNN: An Image is Worth Graph of Nodes NIPS 2022
Augmented Shortcuts for Vision Transformers NIPS 2021
Homogeneous Architecture Augmentation for Neural Predictor ICCV 2021
Learning Frequency Domain Approximation for Binary Neural Networks NIPS 2021
ReNAS: Relativistic Evaluation of Neural Architecture Search CVPR 2021
Manifold Regularized Dynamic Network Pruning CVPR 2021
Reborn Filters: Pruning Convolutional Neural Networks with Limited Data AAAI 2020
SCOP: Scientific Control for Reliable Neural Network Pruning NIPS 2020
A Semi-Supervised Assessor of Neural Architectures CVPR 2020
Neuromorphic Camera Guided High Dynamic Range Imaging CVPR 2020
Frequency Domain Compact 3D Convolutional Neural Networks CVPR 2020
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks AAAI 2020