DIANet: Dense-and-Implicit Attention Network. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Haizhao Yang (AAAI, 2020)

Instance Enhancement Batch Normalization: An Adaptive Regulator of Batch Noise. - Senwei Liang; Zhongzhan Huang; Mingfu Liang; Haizhao Yang (AAAI, 2020)

Convolution-Weight-Distribution Assumption: Rethinking the Criteria of Channel Pruning. - Zhongzhan Huang; Xinjiang Wang; Ping Luo 002 (CoRR, 2020)

Efficient Attention Network: Accelerate Attention by Searching Where to Plug. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Wei He 025; Haizhao Yang (CoRR, 2020)

Blending Pruning Criteria for Convolutional Neural Networks. - Wei He 025; Zhongzhan Huang; Mingfu Liang; Senwei Liang; Haizhao Yang (ICANN (4), 2021)

Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp. - Junfan Lin; Zhongzhan Huang; Keze Wang; Xiaodan Liang; Weiwei Chen; Liang Lin (ICRA, 2021)

Rethinking the Pruning Criteria for Convolutional Neural Network. - Zhongzhan Huang; Wenqi Shao; Xinjiang Wang; Liang Lin; Ping Luo 002 (NeurIPS, 2021)

AlterSGD: Finding Flat Minima for Continual Learning by Alternative Training. - Zhongzhan Huang; Mingfu Liang; Senwei Liang; Wei He 025 (CoRR, 2021)

CEM: Machine-Human Chatting Handoff via Causal-Enhance Module. - ShanShan Zhong; Jinghui Qin; Zhongzhan Huang; Daifeng Li (EMNLP, 2022)

Stiffness-aware neural network for learning Hamiltonian systems. - Senwei Liang; Zhongzhan Huang; Hong Zhang (ICLR, 2022)

The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Wei He 025; Haizhao Yang; Liang Lin (CoRR, 2022)

Accelerating Numerical Solvers for Large-Scale Simulation of Dynamical System via NeurVec. - Zhongzhan Huang; Senwei Liang; Hong Zhang; Haizhao Yang; Liang Lin (CoRR, 2022)

Causal Inference for Chatting Handoff. - ShanShan Zhong; Jinghui Qin; Zhongzhan Huang; Daifeng Li (CoRR, 2022)

Deepening Neural Networks Implicitly and Locally via Recurrent Attention Strategy. - ShanShan Zhong; Wushao Wen; Jinghui Qin; Zhongzhan Huang (CoRR, 2022)

Layer-wise Shared Attention Network on Dynamical System Perspective. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Weiling He; Liang Lin (CoRR, 2022)

Understanding Self-attention Mechanism via Dynamical System Perspective. - Zhongzhan Huang; Mingfu Liang; Jinghui Qin; Shanshan Zhong; Liang Lin (ICCV, 2023)

LSAS: Lightweight Sub-attention Strategy for Alleviating Attention Bias Problem. - Shanshan Zhong; Wushao Wen; Jinghui Qin; Qiangpu Chen; Zhongzhan Huang (ICME, 2023)

SUR-adapter: Enhancing Text-to-Image Pre-trained Diffusion Models with Large Language Models. - Shanshan Zhong; Zhongzhan Huang; Wushao Wen; Jinghui Qin; Liang Lin (ACM Multimedia, 2023)

ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection. - Zhongzhan Huang; Pan Zhou 002; Shuicheng Yan; Liang Lin (NeurIPS, 2023)

On Robust Numerical Solver for ODE via Self-Attention Mechanism. - Zhongzhan Huang; Mingfu Liang; Liang Lin (CoRR, 2023)

ASR: Attention-alike Structural Re-parameterization. - ShanShan Zhong; Zhongzhan Huang; Wushao Wen; Jinghui Qin; Liang Lin (CoRR, 2023)

ESA: Excitation-Switchable Attention for convolutional neural networks. - Shanshan Zhong; Zhongzhan Huang; Wushao Wen; Zhijing Yang; Jinghui Qin (Neurocomputing, 2023)

MoExtend: Tuning New Experts for Modality and Task Extension. - Shanshan Zhong; Shanghua Gao; Zhongzhan Huang; Wushao Wen; Marinka Zitnik; Pan Zhou 002 (ACL (Student Research Workshop), 2024)

Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation. - Shanshan Zhong; Zhongzhan Huang; Shanghua Gao; Wushao Wen; Liang Lin; Marinka Zitnik; Pan Zhou 002 (CVPR, 2024)

Stripe Observation Guided Inference Cost-Free Attention Mechanism. - Zhongzhan Huang; Shanshan Zhong; Wushao Wen; Jinghui Qin; Liang Lin (ECCV (24), 2024)

DEEPAM: Toward Deeper Attention Module in Residual Convolutional Neural Networks. - Shanshan Zhong; Wushao Wen; Jinghui Qin; Zhongzhan Huang (ICANN (1), 2024)

Lottery Ticket Hypothesis for Attention Mechanism in Residual Convolutional Neural Network*. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Wei He 025; Haizhao Yang; Liang Lin (ICME, 2024)

AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios. - Zhongzhan Huang; Mingfu Liang; Shanshan Zhong; Liang Lin (ICML, 2024)

Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima. - Shanshan Zhong; Zhongzhan Huang; Daifeng Li; Wushao Wen; Jinghui Qin; Liang Lin (WWW, 2024)

AnimateZoo: Zero-shot Video Generation of Cross-Species Animation via Subject Alignment. - Yuanfeng Xu; Yuhao Chen; Zhongzhan Huang; Zijian He; Guangrun Wang; Philip Torr 001; Liang Lin (CoRR, 2024)

An Introspective Data Augmentation Method for Training Math Word Problem Solvers. - Jinghui Qin; Zhongzhan Huang; Ying Zeng; Quanshi Zhang; Liang Lin (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models. - Zhongzhan Huang; Guoming Ling; Shanshan Zhong; Hefeng Wu; Liang Lin (ACL (1), 2025)

Anima2: Cross-Species Animal Animation through Image-to-Video Synthesis with Subject Alignment. - Yuanfeng Xu; Yuhao Chen; Zhongzhan Huang; Zijian He; Guangrun Wang; Liang Lin (ICASSP, 2025)

Flat Local Minima for Continual Learning on Semantic Segmentation. - Zhongzhan Huang; Mingfu Liang; Senwei Liang; Shanshan Zhong (MMM (1), 2025)

DVIB: Towards Robust Multimodal Recommender Systems via Variational Information Bottleneck Distillation. - Wenkuan Zhao; Shanshan Zhong; Yifan Liu; Wushao Wen; Jinghui Qin; Mingfu Liang; Zhongzhan Huang (WWW, 2025)

A generic shared attention mechanism for various backbone neural networks. - Zhongzhan Huang; Senwei Liang; Mingfu Liang (Neurocomputing, 2025)

RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs. - Zhongzhan Huang; Guoming Ling; Vincent S. Liang; Yupei Lin; Yandong Chen; Shanshan Zhong; Hefeng Wu; Liang Lin (CoRR, 2025)

A Causality-Aware Paradigm for Evaluating Creativity of Multimodal Large Language Models. - Zhongzhan Huang; Shanshan Zhong; Pan Zhou 002; Shanghua Gao; Marinka Zitnik; Liang Lin (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Continuous Value Assignment: A Doubly Robust Data Augmentation for Off-Policy Learning. - Junfan Lin; Zhongzhan Huang; Keze Wang; Lingbo Liu; Liang Lin (IEEE Trans. Neural Networks Learn. Syst., 2025)

4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos. - Shanshan Zhong; Jiawei Peng; Zehan Zheng; Zhongzhan Huang; Wufei Ma; Guofeng Zhang 025; Qihao Liu; Alan L. Yuille; Jieneng Chen (CoRR, 2025)

AssoCiAm: A Benchmark for Evaluating Association Thinking while Circumventing Ambiguity. - Yifan Liu; Wenkuan Zhao; Shanshan Zhong; Jinghui Qin; Mingfu Liang; Zhongzhan Huang; Wushao Wen (CoRR, 2025)

Multimodal Representation-disentangled Information Bottleneck for Multimodal Recommendation. - Hui Wang; Jinghui Qin; Wushao Wen; Qingling Li; Shanshan Zhong; Zhongzhan Huang (CoRR, 2025)

BridgeDrive: Diffusion Bridge Policy for Closed-Loop Trajectory Planning in Autonomous Driving. - Shu Liu; Wenlin Chen; Weihao Li; Zheng Wang; Lijin Yang; Jianing Huang; Yipin Zhang; Zhongzhan Huang; Ze Cheng; Hao Yang (CoRR, 2025)