Yuxiong He
26 papers · 2018–2026 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (42) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Dynamic Duo
(16)
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Grand Slam
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Deep Specialist
(11)
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Prolific Year Β· Productive
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Unstoppable Β· Bronze
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Century Club Β· Bronze
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Conference Pioneer
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Keyword Collector
(113)
Top co-authors
Research topics
Machine Learning
(23)
Deep Learning
(17)
Optimization & Theory Β· Machine Learning
(15)
Application Areas
(13)
Artificial Intelligence
(10)
Optimization & Theory Β· Deep Learning
(10)
Core AI
(9)
Natural Language Processing
(8)
Techniques
(7)
Learning Types Β· Deep Learning
(5)
Models
(5)
Architectures
(4)
Resources & Methods
(4)
Generation
(3)
Learning Types Β· Machine Learning
(3)
Keywords
model compression
(9)
large language model
(6)
knowledge distillation
(5)
mixture of expert
(3)
weight quantization
(3)
neural network optimization
(3)
inference optimization
(3)
retrieval-augmented generation
(3)
efficient computing
(3)
batch size
(2)
language modeling
(2)
efficient training
(2)
transformer model
(2)
post-training quantization
(2)
adam optimizer
(2)
distributed training
(2)
training efficiency
(2)
model pretraining
(2)
sparse model
(2)
execution feedback
(2)
Papers
GRAD: Generalizing RAG Adaptation with Decoding
ACL 2026
TAGQuant: Token-Aware Clustering for Group-Wise Quantization
EACL 2026
ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments
ICLR 2025
CORD: Balancing COnsistency and Rank Distillation for Robust Retrieval-Augmented Generation
NAACL 2025
Inference Scaling for Bridging Retrieval and Augmented Generation
NAACL 2025
Optimizing Reasoning for Text-to-SQL with Execution Feedback
ACL 2025
STUN: Structured-Then-Unstructured Pruning for Scalable MoE Pruning
ACL 2025
SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation
EMNLP 2025
DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing
AAAI 2024
Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation
AAAI 2024
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
ICLR 2024
DySR: Adaptive Super-Resolution via Algorithm and System Co-design
ICLR 2023
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam
ICLR 2023
Scaling Vision-Language Models with Sparse Mixture of Experts
EMNLP 2023
Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases
ICML 2023
Adversarial Data Augmentation for Task-Specific Knowledge Distillation of Pre-trained Transformers
AAAI 2022
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale
ICML 2022
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
NeurIPS 2022
XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient
NeurIPS 2022
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers
NeurIPS 2022
1-bit Adam: Communication Efficient Large-Scale Training with Adamβs Convergence Speed
ICML 2021
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM
NeurIPS 2021
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement
NeurIPS 2021
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
NeurIPS 2020
Learning Intrinsic Sparse Structures within Long Short-Term Memory
ICLR 2018
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models
NeurIPS 2018