Minjia Zhang
25 papers · 2018–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Academic Marathon (7) π§ Keyword Pioneer π Interdisciplinary Bridge π£ Hot Topic Early Bird
π§
Keyword Pioneer
π£
Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(46)
π€
Dynamic Duo
(11)
π
Grand Slam
π₯
Unstoppable
(6)
π
Century Club
(23)
π
Conference Pioneer
β‘
Prolific Year
(5)
β
The Questioner
ποΈ
Keyword Collector
(113)
Conferences
NIPS (9)
ICLR (4)
AAAI (3)
ACL (3)
EMNLP (2)
NSDI (2)
ICCV (1)
ICML (1)
Top co-authors
Keywords
large language model
(6)
model compression
(6)
knowledge distillation
(5)
efficient computing
(3)
efficient training
(2)
diffusion model
(2)
inference optimization
(2)
distributed training
(2)
preemptible instance
(2)
reinforcement learning
(2)
training efficiency
(2)
in-context learning
(1)
image generation
(1)
question answering
(1)
knowledge transfer
(1)
post-training quantization
(1)
uncertainty quantification
(1)
image editing
(1)
curriculum learning
(1)
model pretraining
(1)
Papers
Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning
AAAI 2026
A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Task
ACL 2026
MedCite: Can Language Models Generate Verifiable Text for Medicine?
ACL 2025
MiniKV: Pushing the Limits of 2-Bit KV Cache via Compression and System Co-Design for Efficient Long Context Inference
ACL 2025
Cache-of-Thought: Master-Apprentice Framework for Cost-Effective Vision Language Model Reasoning
EMNLP 2025
Looking Beyond Text: Reducing Language Bias in Large Vision-Language Models via Multimodal Dual-Attention and Soft-Image Guidance
EMNLP 2025
InstantEdit: Text-Guided Few-Step Image Editing with Piecewise Rectified Flow
ICCV 2025
Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances
NSDI 2024
UltraEdit: Instruction-based Fine-Grained Image Editing at Scale
NIPS 2024
DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing
AAAI 2024
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
ICLR 2024
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam
ICLR 2023
Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs
NSDI 2023
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers
NIPS 2022
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
XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient
NIPS 2022
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
NIPS 2022
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
ICLR 2021
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM
NIPS 2021
HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory
NIPS 2020
AdaTune: Adaptive Tensor Program Compilation Made Efficient
NIPS 2020
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
NIPS 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
NIPS 2018