Yikang Shen

According to our database, Yikang Shen authored at least 70 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Stick-breaking Attention.

Shawn Tan, Yikang Shen, Songlin Yang, Aaron C. Courville, Rameswar Panda

CoRR, 2024

Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler.

Yikang Shen, Matthew Stallone, Mayank Mishra, Gaoyuan Zhang, Shawn Tan, Aditya Prasad, Adriana Meza Soria, David D. Cox, Rameswar Panda

CoRR, 2024

Scaling Granite Code Models to 128K Context.

Matt Stallone, Vaibhav Saxena, Leonid Karlinsky, Bridget McGinn, Tim Bula, Mayank Mishra, Adriana Meza Soria, Gaoyuan Zhang, Aditya Prasad, Yikang Shen, Saptha Surendran, Shanmukha C. Guttula, Hima Patel, Parameswaran Selvam, Xuan-Hong Dang, Yan Koyfman, Atin Sood, Rogério Feris, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda

CoRR, 2024

The infrastructure powering IBM's Gen AI model development.

Talia Gershon, Seetharami Seelam, Brian Belgodere, Milton Bonilla, Lan Hoang, Danny Barnett, I-Hsin Chung, Apoorve Mohan, Ming-Hung Chen, Lixiang Luo, Robert Walkup, Constantinos Evangelinos, Shweta Salaria, Marc Dombrowa, Yoonho Park, Apo Kayi, Liran Schour, Alim Alim, Ali Sydney, Pavlos Maniotis, Laurent Schares, Bernard Metzler, Bengi Karacali-Akyamac, Sophia Wen, Tatsuhiro Chiba, Sunyanan Choochotkaew, Takeshi Yoshimura, Claudia Misale, Tonia Elengikal, Kevin O. Connor, Zhuoran Liu, Richard Molina, Lars Schneidenbach, James Caden, Christopher Laibinis, Carlos Fonseca, Vasily Tarasov, Swaminathan Sundararaman, Frank B. Schmuck, Scott Guthridge, Jeremy Cohn, Marc Eshel, Paul Muench, Runyu Liu, William Pointer, Drew Wyskida, Bob Krull, Ray Rose, Brent Wolfe, William Cornejo, John Walter, Colm Malone, Clifford Perucci, Frank Franco, Nigel Hinds, Bob Calio, Pavel Druyan, Robert Kilduff, John Kienle, Connor McStay, Andrew Figueroa, Matthew Connolly, Edie Fost, Gina Roma, Jake Fonseca, Ido Levy, Michele Payne, Ryan Schenkel, Amir Malki, Lion Schneider, Aniruddha Narkhede, Shekeba Moshref, Alexandra Kisin, Olga Dodin, Bill Rippon, Henry Wrieth, John Ganci, Johnny Colino, Donna Habeger-Rose, Rakesh Pandey, Aditya Gidh, Aditya Gaur, Dennis Patterson, Samsuddin Salmani, Rambilas Varma, Rumana Rumana, Shubham Sharma, Mayank Mishra, Rameswar Panda, Aditya Prasad, Matt Stallone, Gaoyuan Zhang, Yikang Shen, David Cox, Ruchir Puri, Dakshi Agrawal, Drew Thorstensen, Joel Belog, Brent Tang

CoRR, 2024

Octo-planner: On-device Language Model for Planner-Action Agents.

Wei Chen, Zhiyuan Li, Zhen Guo, Yikang Shen

CoRR, 2024

Efficient Continual Pre-training by Mitigating the Stability Gap.

Yiduo Guo, Jie Fu, Huishuai Zhang, Dongyan Zhao, Yikang Shen

CoRR, 2024

Parallelizing Linear Transformers with the Delta Rule over Sequence Length.

Songlin Yang, Bailin Wang, Yu Zhang, Yikang Shen, Yoon Kim

CoRR, 2024

Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training.

Wenyu Du, Tongxu Luo, Zihan Qiu, Zeyu Huang, Yikang Shen, Reynold Cheng, Yike Guo, Jie Fu

CoRR, 2024

Granite Code Models: A Family of Open Foundation Models for Code Intelligence.

Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, S. Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda

CoRR, 2024

JetMoE: Reaching Llama2 Performance with 0.1M Dollars.

Yikang Shen, Zhen Guo, Tianle Cai, Zengyi Qin

CoRR, 2024

Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models.

Bowen Pan, Yikang Shen, Haokun Liu, Mayank Mishra, Gaoyuan Zhang, Aude Oliva, Colin Raffel, Rameswar Panda

CoRR, 2024

Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision.

Zhiqing Sun, Longhui Yu, Yikang Shen, Weiyang Liu, Yiming Yang, Sean Welleck, Chuang Gan

CoRR, 2024

Scattered Mixture-of-Experts Implementation.

Shawn Tan, Yikang Shen, Rameswar Panda, Aaron C. Courville

CoRR, 2024

API Pack: A Massive Multilingual Dataset for API Call Generation.

Zhen Guo, Adriana Meza Soria, Wei Sun, Yikang Shen, Rameswar Panda

CoRR, 2024

Diversity Measurement and Subset Selection for Instruction Tuning Datasets.

Peiqi Wang, Yikang Shen, Zhen Guo, Matthew Stallone, Yoon Kim, Polina Golland, Rameswar Panda

CoRR, 2024

Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble.

Shun Zhang, Zhenfang Chen, Sunli Chen, Yikang Shen, Zhiqing Sun, Chuang Gan

CoRR, 2024

Structured Code Representations Enable Data-Efficient Adaptation of Code Language Models.

Mayank Agarwal, Yikang Shen, Bailin Wang, Yoon Kim, Jie Chen

CoRR, 2024

Gated Linear Attention Transformers with Hardware-Efficient Training.

Songlin Yang, Bailin Wang, Yikang Shen, Rameswar Panda, Yoon Kim

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits.

Chen-Chia Chang, Yikang Shen, Shaoze Fan, Jing Li, Shun Zhang, Ningyuan Cao, Yiran Chen, Xin Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SALMON: Self-Alignment with Instructable Reward Models.

Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David Daniel Cox, Yiming Yang, Chuang Gan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding.

Junyan Li, Delin Chen, Yining Hong, Zhenfang Chen, Peihao Chen, Yikang Shen, Chuang Gan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Consensus Game: Language Model Generation via Equilibrium Search.

Athul Paul Jacob, Yikang Shen, Gabriele Farina, Jacob Andreas

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FlexAttention for Efficient High-Resolution Vision-Language Models.

Junyan Li, Delin Chen, Tianle Cai, Peihao Chen, Yining Hong, Zhenfang Chen, Yikang Shen, Chuang Gan

Proceedings of the Computer Vision - ECCV 2024, 2024

Aligning Large Multimodal Models with Factually Augmented RLHF.

Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liangyan Gui, Yu-Xiong Wang, Yiming Yang, Kurt Keutzer, Trevor Darrell

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Visual Chain-of-Thought Prompting for Knowledge-Based Visual Reasoning.

Zhenfang Chen, Qinhong Zhou, Yikang Shen, Yining Hong, Zhiqing Sun, Dan Gutfreund, Chuang Gan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Autonomous Tree-search Ability of Large Language Models.

Zheyu Zhang, Zhuorui Ye, Yikang Shen, Chuang Gan

CoRR, 2023

SALMON: Self-Alignment with Principle-Following Reward Models.

Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan

CoRR, 2023

GraphText: Graph Reasoning in Text Space.

Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang

CoRR, 2023

An Efficient General-Purpose Modular Vision Model via Multi-Task Heterogeneous Training.

Zitian Chen, Mingyu Ding, Yikang Shen, Wei Zhan, Masayoshi Tomizuka, Erik G. Learned-Miller, Chuang Gan

CoRR, 2023

ModuleFormer: Learning Modular Large Language Models From Uncurated Data.

Yikang Shen, Zheyu Zhang, Tianyou Cao, Shawn Tan, Zhenfang Chen, Chuang Gan

CoRR, 2023

See, Think, Confirm: Interactive Prompting Between Vision and Language Models for Knowledge-based Visual Reasoning.

Zhenfang Chen, Qinhong Zhou, Yikang Shen, Yining Hong, Hao Zhang, Chuang Gan

CoRR, 2023

Adaptive Online Replanning with Diffusion Models.

Siyuan Zhou, Yilun Du, Shun Zhang, Mengdi Xu, Yikang Shen, Wei Xiao, Dit-Yan Yeung, Chuang Gan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision.

Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Planning with Large Language Models for Code Generation.

Shun Zhang, Zhenfang Chen, Yikang Shen, Mingyu Ding, Joshua B. Tenenbaum, Chuang Gan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Hyper-Decision Transformer for Efficient Online Policy Adaptation.

Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, Chuang Gan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Transformer-Patcher: One Mistake Worth One Neuron.

Zeyu Huang, Yikang Shen, Xiaofeng Zhang, Jie Zhou, Wenge Rong, Zhang Xiong

Proceedings of the Eleventh International Conference on Learning Representations, 2023

TextPSG: Panoptic Scene Graph Generation from Textual Descriptions.

Chengyang Zhao, Yikang Shen, Zhenfang Chen, Mingyu Ding, Chuang Gan

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Sparse Universal Transformer.

Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention.

Mingyu Ding, Yikang Shen, Lijie Fan, Zhenfang Chen, Zitian Chen, Ping Luo, Joshua B. Tenenbaum, Chuang Gan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners.

Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik G. Learned-Miller, Chuang Gan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners.

Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik G. Learned-Miller, Chuang Gan

CoRR, 2022

Syntactic Inductive Biases for Deep Learning Methods.

Yikang Shen

CoRR, 2022

Prompting Decision Transformer for Few-Shot Policy Generalization.

Mengdi Xu, Yikang Shen, Shun Zhang, Yuchen Lu, Ding Zhao, Joshua B. Tenenbaum, Chuang Gan

Proceedings of the International Conference on Machine Learning, 2022

Mixture of Attention Heads: Selecting Attention Heads Per Token.

Xiaofeng Zhang, Yikang Shen, Zeyu Huang, Jie Zhou, Wenge Rong, Zhang Xiong

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Unsupervised Dependency Graph Network.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron C. Courville

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Phrase-aware Unsupervised Constituency Parsing.

Xiaotao Gu, Yikang Shen, Jiaming Shen, Jingbo Shang, Jiawei Han

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Self-Instantiated Recurrent Units with Dynamic Soft Recursion.

Aston Zhang, Yi Tay, Yikang Shen, Alvin Chan, Shuai Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Long Range Arena : A Benchmark for Efficient Transformers.

Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, Donald Metzler

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Task Decomposition with Ordered Memory Policy Network.

Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron C. Courville, Joshua B. Tenenbaum, Chuang Gan

Proceedings of the 9th International Conference on Learning Representations, 2021

StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling.

Yikang Shen, Yi Tay, Che Zheng, Dara Bahri, Donald Metzler, Aaron C. Courville

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Explicitly Modeling Syntax in Language Model improves Generalization.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville

CoRR, 2020

Recursive Top-Down Production for Sentence Generation with Latent Trees.

Shawn Tan, Yikang Shen, Alessandro Sordoni, Aaron C. Courville, Timothy J. O'Donnell

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach.

Wenyu Du, Zhouhan Lin, Yikang Shen, Timothy J. O'Donnell, Yoshua Bengio, Yue Zhang

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Investigating Biases in Textual Entailment Datasets.

Shawn Tan, Yikang Shen, Chin-Wei Huang, Aaron C. Courville

CoRR, 2019

Ordered Memory.

Yikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Biological Event Trigger Identification with Noise Contrastive Estimation.

Nan Jiang, Wenge Rong, Yifan Nie, Yikang Shen, Zhang Xiong

IEEE ACM Trans. Comput. Biol. Bioinform., 2018

Generating Contradictory, Neutral, and Entailing Sentences.

Yikang Shen, Shawn Tan, Chin-Wei Huang, Aaron C. Courville

CoRR, 2018

Neural Language Modeling by Jointly Learning Syntax and Lexicon.

Yikang Shen, Zhouhan Lin, Chin-Wei Huang, Aaron C. Courville

Proceedings of the 6th International Conference on Learning Representations, 2018

BanditSum: Extractive Summarization as a Contextual Bandit.

Yue Dong, Yikang Shen, Eric Crawford, Herke van Hoof, Jackie Chi Kit Cheung

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance.

Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron C. Courville, Yoshua Bengio

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Self-organized Hierarchical Softmax.

Yikang Shen, Shawn Tan, Christopher Joseph Pal, Aaron C. Courville

CoRR, 2017

Exploration of Tree-based Hierarchical Softmax for Recurrent Language Models.

Nan Jiang, Wenge Rong, Min Gao, Yikang Shen, Zhang Xiong

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Word Embedding Based Correlation Model for Question/Answer Matching.

Yikang Shen, Wenge Rong, Nan Jiang, Baolin Peng, Jie Tang, Zhang Xiong

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Multidimensional scaling based knowledge provision for new questions in community Question Answering systems.

Siqi Xiang, Wenge Rong, Yikang Shen, Yuanxin Ouyang, Zhang Xiong

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Convolutional Neural Network based sentiment analysis using Adaboost combination.

Yazhi Gao, Wenge Rong, Yikang Shen, Zhang Xiong

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Question/Answer Matching for CQA System via Combining Lexical and Sequential Information.

Yikang Shen, Wenge Rong, Zhiwei Sun, Yuanxin Ouyang, Zhang Xiong

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Influencing Factors Analysis of People's Answering Behaviours on Social Network Based Questions.

Zhiwei Sun, Wenge Rong, Yikang Shen, Yuanxin Ouyang, Chao Li, Zhang Xiong

Proceedings of the 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops, 2014

Choosing the Best Auto-Encoder-Based Bagging Classifier: An Empirical Study.

Yifan Nie, Wenge Rong, Yikang Shen, Chao Li, Zhang Xiong

Proceedings of the Neural Information Processing - 21st International Conference, 2014