← Authors

Qi Meng

24 papers · 2016–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer πŸ† Grand Slam 🀝 Dynamic Duo (18) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (111) ❓ The Questioner (2) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (24) πŸ”₯ Unstoppable (10) πŸ“ˆ Trend Setter

Conferences

IJCAI (5) NIPS (5) ICLR (4) ICML (4) AAAI (2) ACL (2) NAACL (1) UAI (1)

Top co-authors

Tie-yan Liu (18) Wei Chen (16) Zhi-ming Ma (6) Huishuai Zhang (4) Bohan Wang (4) Taifeng Wang (4) Yue Wang (4) Tao Qin (4) Nenghai Yu (3) Shuxin Zheng (3)

Keywords

neural network (4) generalization bound (3) gradient boosting (2) decision tree (2) large language model (2) neural network optimization (2) gradient descent (2) asynchronous stochastic gradient descent (2) graph neural network (2) knowledge distillation (1) semantic analysis (1) neural machine translation (1) convergence analysis (1) distributed learning (1) uncertainty quantification (1) contrastive learning (1) kl divergence (1) continuous optimization (1) batch normalization (1) policy gradient (1)

Papers

Generate or Re-Weight? A Mutual-Guidance Method for Class-Imbalanced Graphs IJCAI 2025
TEACH: A Contrastive Knowledge Adaptive Distillation Framework for Classical Chinese Understanding ACL 2025
HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting ICLR 2025
MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter ACL 2024
$\mathcal{O}$-GNN: incorporating ring priors into molecular modeling ICLR 2023
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition ICML 2023
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations AAAI 2023
SE(3) Equivariant Graph Neural Networks with Complete Local Frames ICML 2022
Does Momentum Change the Implicit Regularization on Separable Data? NIPS 2022
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior ICLR 2022
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks UAI 2021
R-Drop: Regularized Dropout for Neural Networks NIPS 2021
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD NIPS 2021
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks ICML 2021
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost NAACL 2021
I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations IJCAI 2020
Reinforcement Learning with Dynamic Boltzmann Softmax Updates IJCAI 2020
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space ICLR 2019
Capacity Control of ReLU Neural Networks by Basis-Path Norm AAAI 2019
Differential Equations for Modeling Asynchronous Algorithms IJCAI 2018
LightGBM: A Highly Efficient Gradient Boosting Decision Tree NIPS 2017
Asynchronous Stochastic Gradient Descent with Delay Compensation ICML 2017
Asynchronous Accelerated Stochastic Gradient Descent IJCAI 2016
A Communication-Efficient Parallel Algorithm for Decision Tree NIPS 2016