Xin Dong - RankMe

52 papers A* 13A 2Journal 31Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CLIMB: CLustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training. CoRR Shizhe Diao, Yu Yang, Yonggan Fu, Xin Dong, Dan Su, Markus Kliegl, Zijia Chen, Peter Belcak, Yoshi Suhara, Hongxu Yin, Mostofa Patwary, Yingyan Lin, Jan Kautz, Pavlo Molchanov
2025	J	`jnl`	DLER: Doing Length pEnalty Right - Incentivizing More Intelligence per Token via Reinforcement Learning. CoRR Shih-Yang Liu, Xin Dong, Ximing Lu, Shizhe Diao, Mingjie Liu, Min-Hung Chen, Hongxu Yin, Yu-Chiang Frank Wang, Kwang-Ting Cheng, Yejin Choi, Jan Kautz, Pavlo Molchanov
2025	J	`jnl`	Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed. CoRR Yonggan Fu, Lexington Allen Whalen, Zhifan Ye, Xin Dong, Shizhe Diao, Jingyu Liu, Chengyue Wu, Hao Zhang, Enze Xie, Song Han, Maksim Khadkevich, Jan Kautz, Yingyan Celine Lin, Pavlo Molchanov
2025	A*	`conf`	Hymba: A Hybrid-head Architecture for Small Language Models. ICLR Xin Dong, 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, Pavlo Molchanov
2025	A*	`conf`	LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models. ICML Dachuan Shi, Yonggan Fu, Xiangchi Yuan, Zhongzhi Yu, Haoran You, Sixu Li, Xin Dong, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin
2025	J	`jnl`	LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models. CoRR Dachuan Shi, Yonggan Fu, Xiangchi Yuan, Zhongzhi Yu, Haoran You, Sixu Li, Xin Dong, Jan Kautz, Pavlo Molchanov, Yingyan Lin
2025	J	`jnl`	LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement. CoRR Zhifan Ye, Kejing Xia, Yonggan Fu, Xin Dong, Jihoon Hong, Xiangchi Yuan, Shizhe Diao, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin
2025	A*	`conf`	LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement. ICLR Zhifan Ye, Kejing Xia, Yonggan Fu, Xin Dong, Jihoon Hong, Xiangchi Yuan, Shizhe Diao, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin
2025	J	`jnl`	Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models. CoRR Yonggan Fu, Xin Dong, Shizhe Diao, Matthijs Van Keirsbilck, Hanrong Ye, Wonmin Byeon, Yashaswi Karnati, Lucas Liebenwein, Hannah Zhang, Nikolaus Binder, Maksim Khadkevich, Alexander Keller, Jan Kautz, Yingyan (Celine) Lin, Pavlo Molchanov
2025	J	`jnl`	ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models. CoRR Mingjie Liu, Shizhe Diao, Ximing Lu, Jian Hu, Xin Dong, Yejin Choi, Jan Kautz, Yi Dong
2025	J	`jnl`	Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training. CoRR Mingjie Liu, Shizhe Diao, Jian Hu, Ximing Lu, Xin Dong, Hao Zhang, Alexander Bukharin, Shaokun Zhang, Jiaqi Zeng, Makesh Narsimhan Sreedhar, Gerald Shen, David Mosallanezhad, Di Zhang, Jonas Yang, June Yang, Oleksii Kuchaiev, Guilin Liu, Zhiding Yu, Pavlo Molchanov, Yejin Choi, Jan Kautz, Yi Dong
2025	J	`jnl`	Small Language Models are the Future of Agentic AI. CoRR Peter Belcak, Greg Heinrich, Shizhe Diao, Yonggan Fu, Xin Dong, Saurav Muralidharan, Yingyan Celine Lin, Pavlo Molchanov
2025	J	`jnl`	TiDAR: Think in Diffusion, Talk in Autoregression. CoRR Jingyu Liu, Xin Dong, Zhifan Ye, Rishabh Mehta, Yonggan Fu, Vartika Singh, Jan Kautz, Ce Zhang, Pavlo Molchanov
2025	J	`jnl`	ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration. CoRR Hongjin Su, Shizhe Diao, Ximing Lu, Mingjie Liu, Jiacheng Xu, Xin Dong, Yonggan Fu, Peter Belcak, Hanrong Ye, Hongxu Yin, Yi Dong, Evelina Bakhturina, Tao Yu, Yejin Choi, Jan Kautz, Pavlo Molchanov
2024	—	`conf`	A Simple Background Augmentation Method for Object Detection with Diffusion Model. ECCV (66) Yuhang Li, Xin Dong, Chen Chen, Weiming Zhuang, Lingjuan Lyu
2024	J	`jnl`	A Simple Background Augmentation Method for Object Detection with Diffusion Model. CoRR Yuhang Li, Xin Dong, Chen Chen, Weiming Zhuang, Lingjuan Lyu
2024	J	`jnl`	A deeper look at depth pruning of LLMs. CoRR Shoaib Ahmed Siddiqui, Xin Dong, Greg Heinrich, Thomas M. Breuel, Jan Kautz, David Krueger, Pavlo Molchanov
2024	J	`jnl`	Error-Aware Conversion from ANN to SNN via Post-training Parameter Calibration. Int. J. Comput. Vis. Yuhang Li, Shikuang Deng, Xin Dong, Shi Gu
2024	—	`conf`	Finding Needles in a Haystack: A Black-Box Approach to Invisible Watermark Detection. ECCV (33) Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin
2024	J	`jnl`	Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection. CoRR Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin
2024	J	`jnl`	Hymba: A Hybrid-head Architecture for Small Language Models. CoRR Xin Dong, Yonggan Fu, Shizhe Diao, Wonmin Byeon, Zijia Chen, Ameya Sunil Mahabaleshwarkar, Shih-Yang Liu, Matthijs Van Keirsbilck, Min-Hung Chen, Yoshi Suhara, Yingyan Lin, Jan Kautz, Pavlo Molchanov
2024	J	`jnl`	Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization. CoRR Yuhang Li, Xin Dong, Chen Chen, Jingtao Li, Yuxin Wen, Michael Spranger, Lingjuan Lyu
2023	A*	`conf`	Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning. NeurIPS Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long
2022	J	`jnl`	Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration. CoRR Yuhang Li, Shikuang Deng, Xin Dong, Shi Gu
2022	J	`jnl`	DRESS: Dynamic REal-time Sparse Subnets. CoRR Zhongnan Qu, Syed Shakib Sarwar, Xin Dong, Yuecheng Li, Huseyin Ekin Sumbul, Barbara De Salvo
2022	A*	`conf`	Neural Mean Discrepancy for Efficient Out-of-Distribution Detection. CVPR Xin Dong, Junfeng Guo, Ang Li, Wei-Te Ting, Cong Liu, H. T. Kung
2022	A	`conf`	Privacy Vulnerability of Split Computing to Data-Free Model Inversion Attacks. BMVC Xin Dong, Hongxu Yin, José M. Álvarez, Jan Kautz, Pavlo Molchanov, H. T. Kung
2022	—	`conf`	SphereFed: Hyperspherical Federated Learning. ECCV (26) Xin Dong, Sai Qian Zhang, Ang Li, H. T. Kung
2022	J	`jnl`	SphereFed: Hyperspherical Federated Learning. CoRR Xin Dong, Sai Qian Zhang, Ang Li, H. T. Kung
2022	A*	`conf`	SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems. CVPR Xin Dong, Barbara De Salvo, Meng Li, Chiao Liu, Zhongnan Qu, H. T. Kung, Ziyun Li
2022	J	`jnl`	SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems. CoRR Xin Dong, Barbara De Salvo, Meng Li, Chiao Liu, Zhongnan Qu, H. T. Kung, Ziyun Li
2021	A*	`conf`	A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration. ICML Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu
2021	J	`jnl`	A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration. CoRR Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu
2021	J	`jnl`	Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion. CoRR Xin Dong, Hongxu Yin, José M. Álvarez, Jan Kautz, Pavlo Molchanov
2021	J	`jnl`	Lightweight Detection of Out-of-Distribution and Adversarial Samples via Channel Mean Discrepancy. CoRR Xin Dong, Junfeng Guo, Wei-Te Ting, H. T. Kung
2021	A*	`conf`	MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing. ICCV Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Xin Dong, Fengwei Yu, Shaoqing Lu, Shi Gu
2021	A*	`conf`	Training for multi-resolution inference using reusable quantization terms. ASPLOS Sai Qian Zhang, Bradley McDanel, H. T. Kung, Xin Dong
2020	A*	`conf`	Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks. ICLR Yuhang Li, Xin Dong, Wei Wang
2020	J	`jnl`	Efficient Bitwidth Search for Practical Mixed Precision Neural Network. CoRR Yuhang Li, Wei Wang, Haoli Bai, Ruihao Gong, Xin Dong, Fengwei Yu
2020	A*	`conf`	RTN: Reparameterized Ternary Network. AAAI Yuhang Li, Xin Dong, Sai Qian Zhang, Haoli Bai, Yuanpeng Chen, Wei Wang
2020	—	`conf`	exBERT: Extending Pre-trained Models with Domain-specific Vocabulary Under Constrained Training Resources. EMNLP (Findings) Wen Tai, H. T. Kung, Xin Dong, Marcus Z. Comiter, Chang-Fu Kuo
2019	A*	`conf`	A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks. CVPR Yinghao Xu, Xin Dong, Yudian Li, Hao Su
2019	J	`jnl`	Additive Powers-of-Two Quantization: A Non-uniform Discretization for Neural Networks. CoRR Yuhang Li, Xin Dong, Wei Wang
2019	A*	`conf`	Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit? CVPR Shilin Zhu, Xin Dong, Hao Su
2019	J	`jnl`	Full-stack Optimization for Accelerating CNNs with FPGA Validation. CoRR Bradley McDanel, Sai Qian Zhang, H. T. Kung, Xin Dong
2019	A	`conf`	Full-stack optimization for accelerating CNNs using powers-of-two weights with FPGA validation. ICS Bradley McDanel, Sai Qian Zhang, H. T. Kung, Xin Dong
2019	—	`conf`	Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays. ASAP H. T. Kung, Bradley McDanel, Sai Qian Zhang, Xin Dong, Chih-Chiang Chen
2019	J	`jnl`	RTN: Reparameterized Ternary Network. CoRR Yuhang Li, Xin Dong, Sai Qian Zhang, Haoli Bai, Yuanpeng Chen, Wei Wang
2018	J	`jnl`	A Main/Subsidiary Network Framework for Simplifying Binary Neural Network. CoRR Yinghao Xu, Xin Dong, Yudian Li, Hao Su
2018	J	`jnl`	Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit? CoRR Shilin Zhu, Xin Dong, Hao Su
2017	—	`conf`	Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon. NIPS Xin Dong, Shangyu Chen, Sinno Jialin Pan
2017	J	`jnl`	Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon. CoRR Xin Dong, Shangyu Chen, Sinno Jialin Pan