Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon. - Xin Dong 009; Shangyu Chen; Sinno Jialin Pan (NIPS, 2017)

A Main/Subsidiary Network Framework for Simplifying Binary Neural Network. - Yinghao Xu; Xin Dong 009; Yudian Li; Hao Su (CoRR, 2018)

Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays. - H. T. Kung 001; Bradley McDanel; Sai Qian Zhang; Xin Dong 009; Chih-Chiang Chen (ASAP, 2019)

A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks. - Yinghao Xu; Xin Dong 009; Yudian Li; Hao Su (CVPR, 2019)

Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit? - Shilin Zhu; Xin Dong 009; Hao Su 001 (CVPR, 2019)

Full-stack optimization for accelerating CNNs using powers-of-two weights with FPGA validation. - Bradley McDanel; Sai Qian Zhang; H. T. Kung 001; Xin Dong 009 (ICS, 2019)

Full-stack Optimization for Accelerating CNNs with FPGA Validation. - Bradley McDanel; Sai Qian Zhang; H. T. Kung 001; Xin Dong 009 (CoRR, 2019)

Additive Powers-of-Two Quantization: A Non-uniform Discretization for Neural Networks. - Yuhang Li 001; Xin Dong 009; Wei Wang 059 (CoRR, 2019)

RTN: Reparameterized Ternary Network. - Yuhang Li 001; Xin Dong 009; Sai Qian Zhang; Haoli Bai; Yuanpeng Chen; Wei Wang 059 (AAAI, 2020)

exBERT: Extending Pre-trained Models with Domain-specific Vocabulary Under Constrained Training Resources. - Wen Tai; H. T. Kung 001; Xin Dong 009; Marcus Z. Comiter; Chang-Fu Kuo (EMNLP (Findings), 2020)

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks. - Yuhang Li 001; Xin Dong 009; Wei Wang 059 (ICLR, 2020)

Efficient Bitwidth Search for Practical Mixed Precision Neural Network. - Yuhang Li 001; Wei Wang 059; Haoli Bai; Ruihao Gong; Xin Dong 009; Fengwei Yu (CoRR, 2020)

Training for multi-resolution inference using reusable quantization terms. - Sai Qian Zhang; Bradley McDanel; H. T. Kung 001; Xin Dong 009 (ASPLOS, 2021)

MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing. - Yuhang Li 001; Feng Zhu 006; Ruihao Gong; Mingzhu Shen; Xin Dong 009; Fengwei Yu; Shaoqing Lu; Shi Gu (ICCV, 2021)

A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration. - Yuhang Li 001; Shikuang Deng; Xin Dong 009; Ruihao Gong; Shi Gu (ICML, 2021)

Lightweight Detection of Out-of-Distribution and Adversarial Samples via Channel Mean Discrepancy. - Xin Dong 009; Junfeng Guo; Wei-Te Ting; H. T. Kung 001 (CoRR, 2021)

Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion. - Xin Dong 009; Hongxu Yin; José M. Álvarez 004; Jan Kautz; Pavlo Molchanov 001 (CoRR, 2021)

Privacy Vulnerability of Split Computing to Data-Free Model Inversion Attacks. - Xin Dong 009; Hongxu Yin; José M. Álvarez 004; Jan Kautz; Pavlo Molchanov 001; H. T. Kung 001 (BMVC, 2022)

Neural Mean Discrepancy for Efficient Out-of-Distribution Detection. - Xin Dong 009; Junfeng Guo; Ang Li; Wei-Te Ting; Cong Liu 005; H. T. Kung 001 (CVPR, 2022)

SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems. - Xin Dong 009; Barbara De Salvo; Meng Li 004; Chiao Liu; Zhongnan Qu; H. T. Kung 001; Ziyun Li (CVPR, 2022)

SphereFed: Hyperspherical Federated Learning. - Xin Dong 009; Sai Qian Zhang; Ang Li; H. T. Kung 001 (ECCV (26), 2022)

Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration. - Yuhang Li 001; Shikuang Deng; Xin Dong 009; Shi Gu (CoRR, 2022)

DRESS: Dynamic REal-time Sparse Subnets. - Zhongnan Qu; Syed Shakib Sarwar; Xin Dong 009; Yuecheng Li; Huseyin Ekin Sumbul; Barbara De Salvo (CoRR, 2022)

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning. - Yue Tan; Chen Chen 043; Weiming Zhuang; Xin Dong 009; Lingjuan Lyu; Guodong Long (NeurIPS, 2023)

A Simple Background Augmentation Method for Object Detection with Diffusion Model. - Yuhang Li 001; Xin Dong 009; Chen Chen 043; Weiming Zhuang; Lingjuan Lyu (ECCV (66), 2024)

Finding Needles in a Haystack: A Black-Box Approach to Invisible Watermark Detection. - Minzhou Pan; Zhenting Wang; Xin Dong 009; Vikash Sehwag; Lingjuan Lyu; Xue Lin 001 (ECCV (33), 2024)

Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization. - Yuhang Li 001; Xin Dong 009; Chen Chen 043; Jingtao Li; Yuxin Wen; Michael Spranger; Lingjuan Lyu (CoRR, 2024)

A deeper look at depth pruning of LLMs. - Shoaib Ahmed Siddiqui; Xin Dong 009; Greg Heinrich; Thomas M. Breuel; Jan Kautz; David Krueger 001; Pavlo Molchanov 001 (CoRR, 2024)

Error-Aware Conversion from ANN to SNN via Post-training Parameter Calibration. - Yuhang Li 001; Shikuang Deng; Xin Dong 009; Shi Gu (Int. J. Comput. Vis., 2024)

Hymba: A Hybrid-head Architecture for Small Language Models. - Xin Dong 009; Yonggan Fu; Shizhe Diao; Wonmin Byeon; Zijia Chen; Ameya Sunil Mahabaleshwarkar; Shih-Yang Liu; Matthijs Van Keirsbilck; Min-Hung Chen; Yoshi Suhara; Yingyan Celine Lin; Jan Kautz; et al. (ICLR, 2025)

LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement. - Zhifan Ye; Kejing Xia; Yonggan Fu; Xin Dong 009; Jihoon Hong; Xiangchi Yuan; Shizhe Diao; Jan Kautz; Pavlo Molchanov 001; Yingyan Celine Lin (ICLR, 2025)

CLIMB: CLustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training. - Shizhe Diao; Yu Yang; Yonggan Fu; Xin Dong 009; Dan Su 003; Markus Kliegl; Zijia Chen; Peter Belcak; Yoshi Suhara; Hongxu Yin; Mostofa Patwary; Yingyan Lin; et al. (CoRR, 2025)

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models. - Mingjie Liu; Shizhe Diao; Ximing Lu; Jian Hu; Xin Dong 009; Yejin Choi 001; Jan Kautz; Yi Dong (CoRR, 2025)

Small Language Models are the Future of Agentic AI. - Peter Belcak; Greg Heinrich; Shizhe Diao; Yonggan Fu; Xin Dong 009; Saurav Muralidharan; Yingyan Celine Lin; Pavlo Molchanov 001 (CoRR, 2025)

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training. - Mingjie Liu; Shizhe Diao; Jian Hu; Ximing Lu; Xin Dong 009; Hao Zhang 097; Alexander Bukharin; Shaokun Zhang; Jiaqi Zeng; Makesh Narsimhan Sreedhar; Gerald Shen; David Mosallanezhad; et al. (CoRR, 2025)

LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models. - Dachuan Shi; Yonggan Fu; Xiangchi Yuan; Zhongzhi Yu; Haoran You; Sixu Li; Xin Dong 009; Jan Kautz; Pavlo Molchanov 001; Yingyan Lin (CoRR, 2025)