Choosing the Best Auto-Encoder-Based Bagging Classifier: An Empirical Study. - Yifan Nie; Wenge Rong; Yikang Shen; Chao Li 001; Zhang Xiong 001 (ICONIP (1), 2014)

Influencing Factors Analysis of People's Answering Behaviours on Social Network Based Questions. - Zhiwei Sun; Wenge Rong; Yikang Shen; Yuanxin Ouyang; Chao Li 001; Zhang Xiong 001 (UIC/ATC/ScalCom, 2014)

Question/Answer Matching for CQA System via Combining Lexical and Sequential Information. - Yikang Shen; Wenge Rong; Zhiwei Sun; Yuanxin Ouyang; Zhang Xiong 001 (AAAI, 2015)

Convolutional Neural Network based sentiment analysis using Adaboost combination. - Yazhi Gao; Wenge Rong; Yikang Shen; Zhang Xiong 001 (IJCNN, 2016)

Multidimensional scaling based knowledge provision for new questions in community Question Answering systems. - Siqi Xiang; Wenge Rong; Yikang Shen; Yuanxin Ouyang; Zhang Xiong 001 (IJCNN, 2016)

Word Embedding Based Correlation Model for Question/Answer Matching. - Yikang Shen; Wenge Rong; Nan Jiang 010; Baolin Peng; Jie Tang 001; Zhang Xiong 001 (AAAI, 2017)

Exploration of Tree-based Hierarchical Softmax for Recurrent Language Models. - Nan Jiang 010; Wenge Rong; Min Gao 001; Yikang Shen; Zhang Xiong 001 (IJCAI, 2017)

Self-organized Hierarchical Softmax. - Yikang Shen; Shawn Tan; Christopher Joseph Pal; Aaron C. Courville (CoRR, 2017)

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. - Yikang Shen; Zhouhan Lin; Athul Paul Jacob; Alessandro Sordoni; Aaron C. Courville; Yoshua Bengio (ACL (1), 2018)

BanditSum: Extractive Summarization as a Contextual Bandit. - Yue Dong 002; Yikang Shen; Eric Crawford; Herke van Hoof; Jackie Chi Kit Cheung (EMNLP, 2018)

Neural Language Modeling by Jointly Learning Syntax and Lexicon. - Yikang Shen; Zhouhan Lin; Chin-Wei Huang; Aaron C. Courville (ICLR (Poster), 2018)

Generating Contradictory, Neutral, and Entailing Sentences. - Yikang Shen; Shawn Tan; Chin-Wei Huang; Aaron C. Courville (CoRR, 2018)

Biological Event Trigger Identification with Noise Contrastive Estimation. - Nan Jiang 010; Wenge Rong; Yifan Nie; Yikang Shen; Zhang Xiong 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Aaron C. Courville (ICLR, 2019)

Ordered Memory. - Yikang Shen; Shawn Tan; Seyed Arian Hosseini; Zhouhan Lin; Alessandro Sordoni; Aaron C. Courville (NeurIPS, 2019)

Investigating Biases in Textual Entailment Datasets. - Shawn Tan; Yikang Shen; Chin-Wei Huang; Aaron C. Courville (CoRR, 2019)

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 004 (ACL, 2020)

Recursive Top-Down Production for Sentence Generation with Latent Trees. - Shawn Tan; Yikang Shen; Alessandro Sordoni; Aaron C. Courville; Timothy J. O'Donnell (EMNLP (Findings), 2020)

Explicitly Modeling Syntax in Language Model improves Generalization. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Siva Reddy; Aaron C. Courville (CoRR, 2020)

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 (ACL/IJCNLP (1), 2021)

Learning Task Decomposition with Ordered Memory Policy Network. - Yuchen Lu; Yikang Shen; Siyuan Zhou; Aaron C. Courville; Joshua B. Tenenbaum; Chuang Gan 001 (ICLR, 2021)

Long Range Arena : A Benchmark for Efficient Transformers. - Yi Tay; Mostafa Dehghani 001; Samira Abnar; Yikang Shen; Dara Bahri; Philip Pham; Jinfeng Rao; Liu Yang; Sebastian Ruder; Donald Metzler (ICLR, 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 (NAACL-HLT, 2021)

Self-Instantiated Recurrent Units with Dynamic Soft Recursion. - Aston Zhang; Yi Tay; Yikang Shen; Alvin Chan; Shuai Zhang 007 (NeurIPS, 2021)

Phrase-aware Unsupervised Constituency Parsing. - Xiaotao Gu; Yikang Shen; Jiaming Shen; Jingbo Shang; Jiawei Han 001 (ACL (1), 2022)

Unsupervised Dependency Graph Network. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Peng Li; Jie Zhou; Aaron C. Courville (ACL (1), 2022)

Mixture of Attention Heads: Selecting Attention Heads Per Token. - Xiaofeng Zhang 004; Yikang Shen; Zeyu Huang; Jie Zhou; Wenge Rong; Zhang Xiong 001 (EMNLP, 2022)

Prompting Decision Transformer for Few-Shot Policy Generalization. - Mengdi Xu; Yikang Shen; Shun Zhang; Yuchen Lu; Ding Zhao; Joshua B. Tenenbaum; Chuang Gan 001 (ICML, 2022)

Syntactic Inductive Biases for Deep Learning Methods. - Yikang Shen (CoRR, 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 001 (CoRR, 2022)

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 001 (CVPR, 2023)

Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention. - Mingyu Ding; Yikang Shen; Lijie Fan; Zhenfang Chen; Zitian Chen; Ping Luo 002; Joshua B. Tenenbaum; Chuang Gan 001 (CVPR, 2023)

Sparse Universal Transformer. - Shawn Tan; Yikang Shen; Zhenfang Chen; Aaron C. Courville; Chuang Gan 001 (EMNLP, 2023)

TextPSG: Panoptic Scene Graph Generation from Textual Descriptions. - Chengyang Zhao; Yikang Shen; Zhenfang Chen; Mingyu Ding; Chuang Gan 001 (ICCV, 2023)

Transformer-Patcher: One Mistake Worth One Neuron. - Zeyu Huang; Yikang Shen; Xiaofeng Zhang 004; Jie Zhou; Wenge Rong; Zhang Xiong 001 (ICLR, 2023)

Hyper-Decision Transformer for Efficient Online Policy Adaptation. - Mengdi Xu; Yuchen Lu; Yikang Shen; Shun Zhang; Ding Zhao; Chuang Gan 001 (ICLR, 2023)

Planning with Large Language Models for Code Generation. - Shun Zhang; Zhenfang Chen; Yikang Shen; Mingyu Ding; Joshua B. Tenenbaum; Chuang Gan 001 (ICLR, 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 001 (NeurIPS, 2023)

Adaptive Online Replanning with Diffusion Models. - Siyuan Zhou; Yilun Du; Shun Zhang; Mengdi Xu; Yikang Shen; Wei Xiao 003; Dit-Yan Yeung; Chuang Gan 001 (NeurIPS, 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 001 (CoRR, 2023)

ModuleFormer: Learning Modular Large Language Models From Uncurated Data. - Yikang Shen; Zheyu Zhang; Tianyou Cao; Shawn Tan; Zhenfang Chen; Chuang Gan 001 (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 001 (CoRR, 2023)

GraphText: Graph Reasoning in Text Space. - Jianan Zhao 002; Le Zhuo; Yikang Shen; Meng Qu; Kai Liu; Michael M. Bronstein; Zhaocheng Zhu; Jian Tang 005 (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 001 (CoRR, 2023)

Autonomous Tree-search Ability of Large Language Models. - Zheyu Zhang; Zhuorui Ye; Yikang Shen; Chuang Gan 001 (CoRR, 2023)

Visual Chain-of-Thought Prompting for Knowledge-Based Visual Reasoning. - Zhenfang Chen; Qinhong Zhou; Yikang Shen; Yining Hong; Zhiqing Sun; Dan Gutfreund; Chuang Gan 001 (AAAI, 2024)

Aligning Large Multimodal Models with Factually Augmented RLHF. - Zhiqing Sun; Sheng Shen 001; Shengcao Cao; Haotian Liu; Chunyuan Li; Yikang Shen; Chuang Gan 001; Liangyan Gui; Yu-Xiong Wang; Yiming Yang; Kurt Keutzer; Trevor Darrell (ACL (Findings), 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 001 (ECCV (25), 2024)

The Consensus Game: Language Model Generation via Equilibrium Search. - Athul Paul Jacob; Yikang Shen; Gabriele Farina; Jacob Andreas (ICLR, 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 001 (ICLR, 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 001 (ICLR, 2024)

LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits. - Chen-Chia Chang; Yikang Shen; Shaoze Fan; Jing Li 025; Shun Zhang; Ningyuan Cao; Yiran Chen 001; Xin Zhang 025 (ICML, 2024)

Gated Linear Attention Transformers with Hardware-Efficient Training. - Songlin Yang; Bailin Wang; Yikang Shen; Rameswar Panda; Yoon Kim (ICML, 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 001 (NeurIPS, 2024)

Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision. - Zhiqing Sun; Longhui Yu; Yikang Shen; Weiyang Liu; Yiming Yang; Sean Welleck; Chuang Gan 001 (NeurIPS, 2024)

Parallelizing Linear Transformers with the Delta Rule over Sequence Length. - Songlin Yang; Bailin Wang; Yu Zhang; Yikang Shen; Yoon Kim (NeurIPS, 2024)

Structured Code Representations Enable Data-Efficient Adaptation of Code Language Models. - Mayank Agarwal; Yikang Shen; Bailin Wang; Yoon Kim; Jie Chen (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 001 (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)

API Pack: A Massive Multilingual Dataset for API Call Generation. - Zhen Guo; Adriana Meza Soria; Wei Sun; Yikang Shen; Rameswar Panda (CoRR, 2024)

Scattered Mixture-of-Experts Implementation. - Shawn Tan; Yikang Shen; Rameswar Panda; Aaron C. Courville (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)

JetMoE: Reaching Llama2 Performance with 0.1M Dollars. - Yikang Shen; Zhen Guo; Tianle Cai; Zengyi Qin (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; et al. (CoRR, 2024)

Efficient Continual Pre-training by Mitigating the Stability Gap. - Yiduo Guo; Jie Fu; Huishuai Zhang; Dongyan Zhao 001; Yikang Shen (CoRR, 2024)

Octo-planner: On-device Language Model for Planner-Action Agents. - Wei Chen; Zhiyuan Li; Zhen Guo; Yikang Shen (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; et al. (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; et al. (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)

Stick-breaking Attention. - Shawn Tan; Yikang Shen; Songlin Yang; Aaron C. Courville; Rameswar Panda (CoRR, 2024)

API Pack: A Massive Multi-Programming Language Dataset for API Call Generation. - Zhen Guo; Adriana Meza Soria; Wei Sun; Yikang Shen; Rameswar Panda (ICLR, 2025)

Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study. - Shawn Tan; Songlin Yang; Aaron C. Courville; Rameswar Panda; Yikang Shen (ICLR, 2025)

Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization. - Wei Liu; Anweshit Panda; Ujwal Pandey; Christopher Brissette; Yikang Shen; George M. Slota; Naigang Wang; Jie Chen; Yangyang Xu (Trans. Mach. Learn. Res., 2025)

Do Larger Language Models Imply Better Reasoning? A Pretraining Scaling Law for Reasoning. - Xinyi Wang 003; Shawn Tan; Mingyu Jin; William Yang Wang; Rameswar Panda; Yikang Shen (CoRR, 2025)

PaTH Attention: Position Encoding via Accumulating Householder Transformations. - Songlin Yang; Yikang Shen; Kaiyue Wen; Shawn Tan; Mayank Mishra; Liliang Ren; Rameswar Panda; Yoon Kim (CoRR, 2025)

Synthetic Data RL: Task Definition Is All You Need. - Yiduo Guo; Zhen Guo; Chuanwei Huang; Zi-Ang Wang; Zekai Zhang; Haofei Yu; Huishuai Zhang; Yikang Shen (CoRR, 2025)

FlashFormer: Whole-Model Kernels for Efficient Low-Batch Inference. - Aniruddha Nrusimha; William Brandon; Mayank Mishra; Yikang Shen; Rameswar Panda; Jonathan Ragan-Kelley; Yoon Kim (CoRR, 2025)

LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation. - Chen-Chia Chang; Wan-Hsuan Lin; Yikang Shen; Yiran Chen 001; Xin Zhang 025 (CoRR, 2025)