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2020 – today
- 2024
[c47]Kaixin Li, Qisheng Hu, James Xu Zhao, Hui Chen, Yuxi Xie, Tiedong Liu, Michael Shieh, Junxian He:
InstructCoder: Instruction Tuning Large Language Models for Code Editing. ACL (Student Research Workshop) 2024: 50-70- [c46]Do Xuan Long, Yiran Zhao, Hannah Brown, Yuxi Xie, James Xu Zhao, Nancy F. Chen, Kenji Kawaguchi, Michael Shieh, Junxian He:
Prompt Optimization via Adversarial In-Context Learning. ACL (1) 2024: 7308-7327 - [c45]Wenxuan Ding, Weiqi Wang, Sze Heng Douglas Kwok, Minghao Liu, Tianqing Fang, Jiaxin Bai, Xin Liu, Changlong Yu, Zheng Li, Chen Luo, Qingyu Yin, Bing Yin, Junxian He, Yangqiu Song:
IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension Abilities of Language Models in E-commerce. EMNLP (Findings) 2024: 2247-2266 - [c44]Bryan Wilie, Samuel Cahyawijaya, Etsuko Ishii, Junxian He, Pascale Fung:
Belief Revision: The Adaptability of Large Language Models Reasoning. EMNLP 2024: 10480-10496 - [c43]Junteng Liu, Shiqi Chen, Yu Cheng, Junxian He:
On the Universal Truthfulness Hyperplane Inside LLMs. EMNLP 2024: 18199-18224 - [c42]Wei Liu
, Weihao Zeng, Keqing He, Yong Jiang, Junxian He:
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning. ICLR 2024 - [c41]Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi:
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs. ICLR 2024 - [c40]Shiqi Chen, Miao Xiong, Junteng Liu, Zhengxuan Wu, Teng Xiao, Siyang Gao, Junxian He:
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation. ICML 2024 - [c39]Cheng Deng, Tianhang Zhang, Zhongmou He, Qiyuan Chen, Yuanyuan Shi, Yi Xu, Luoyi Fu, Weinan Zhang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin, Junxian He:
K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization. WSDM 2024: 161-170 - [i48]Zhouhan Lin, Cheng Deng, Le Zhou, Tianhang Zhang, Yi Xu, Yutong Xu, Zhongmou He, Yuanyuan Shi, Beiya Dai, Yunchong Song, Boyi Zeng, Qiyuan Chen, Tao Shi, Tianyu Huang, Yiwei Xu, Shu Wang, Luoyi Fu, Weinan Zhang, Junxian He, Chao Ma, Yunqiang Zhu, Xinbing Wang, Chenghu Zhou:
GeoGalactica: A Scientific Large Language Model in Geoscience. CoRR abs/2401.00434 (2024) - [i47]Chang Ma, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang, Yaohui Jin, Zhenzhong Lan, Lingpeng Kong, Junxian He:
AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents. CoRR abs/2401.13178 (2024) - [i46]Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi:
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models. CoRR abs/2402.03271 (2024) - [i45]Shiqi Chen, Miao Xiong, Junteng Liu, Zhengxuan Wu, Teng Xiao, Siyang Gao, Junxian He:
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation. CoRR abs/2403.01548 (2024) - [i44]Yuzhen Huang, Jinghan Zhang, Zifei Shan, Junxian He:
Compression Represents Intelligence Linearly. CoRR abs/2404.09937 (2024) - [i43]Wenxuan Ding, Weiqi Wang, Sze Heng Douglas Kwok, Minghao Liu, Tianqing Fang, Jiaxin Bai, Junxian He, Yangqiu Song:
IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension Abilities of Language Models in E-commerce. CoRR abs/2406.10173 (2024) - [i42]Bryan Wilie, Samuel Cahyawijaya, Etsuko Ishii, Junxian He, Pascale Fung:
Belief Revision: The Adaptability of Large Language Models Reasoning. CoRR abs/2406.19764 (2024) - [i41]Junteng Liu, Shiqi Chen, Yu Cheng, Junxian He:
On the Universal Truthfulness Hyperplane Inside LLMs. CoRR abs/2407.08582 (2024) - [i40]Yuxuan Tong, Xiwen Zhang, Rui Wang, Ruidong Wu, Junxian He:
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving. CoRR abs/2407.13690 (2024) - [i39]Junxian He, Shrinivas J. Pundlik, Gang Luo:
Can ChatGPT assist visually impaired people with micro-navigation? CoRR abs/2408.08321 (2024) - 2023
- [j7]Cong Shi, Junxian He, Shrinivas J. Pundlik, Xichuan Zhou, Nanjian Wu, Gang Luo:
Low-cost real-time VLSI system for high-accuracy optical flow estimation using biological motion features and random forests. Sci. China Inf. Sci. 66(5) (2023) - [j6]Leyi Chen, Cong Shi, Junxian He, Jianyi Yu, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Min Tian:
An 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips. IEEE Trans. Circuits Syst. I Regul. Pap. 70(11): 4249-4259 (2023) - [j5]Cong Shi, Jingya Zhang, Tengxiao Wang, Zhengqing Zhong, Junxian He, Haoran Gao, Jianyi Yu, Ping Li, Min Tian:
An Edge Neuromorphic Hardware With Fast On-Chip Error-Triggered Learning on Compressive Sensed Spikes. IEEE Trans. Circuits Syst. II Express Briefs 70(7): 2665-2669 (2023) - [c38]Zhengqing Zhong, Tengxiao Wang, Haibing Wang, Zhihua Zhou, Junxian He, Fang Tang, Xichuan Zhou, Shuangming Yu, Liyuan Liu, Nanjian Wu, Min Tian, Cong Shi:
Live Demonstration: Face Recognition at The Edge Using Fast On-Chip Deep Learning Neuromorphic Chip. AICAS 2023: 1-2 - [c37]Tengxiao Wang, Min Tian, Zhengqing Zhong, Haibing Wang, Junxian He, Fang Tang, Xichuan Zhou, Shuangming Yu, Nanjian Wu, Liyuan Liu, Cong Shi:
MorphBungee: A 65nm 7.2mm2 27μJ/image Digital Edge Neuromorphic Chip with On-Chip 802 Frame/s Multi-Layer Spiking Neural Network Learning. A-SSCC 2023: 1-3 - [c36]James Xu Zhao, Yuxi Xie, Kenji Kawaguchi, Junxian He, Michael Qizhe Xie:
Automatic Model Selection with Large Language Models for Reasoning. EMNLP (Findings) 2023: 758-783 - [c35]Junlei Zhang, Zhenzhong Lan, Junxian He:
Contrastive Learning of Sentence Embeddings from Scratch. EMNLP 2023: 3916-3932 - [c34]Niloofar Mireshghallah, Nikolai Vogler, Junxian He, Omar Florez, Ahmed El-Kishky, Taylor Berg-Kirkpatrick:
Simple Temporal Adaptation to Changing Label Sets: Hashtag Prediction via Dense KNN. EMNLP 2023: 7302-7311 - [c33]Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer:
Mega: Moving Average Equipped Gated Attention. ICLR 2023 - [c32]Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He:
FELM: Benchmarking Factuality Evaluation of Large Language Models. NeurIPS 2023 - [c31]Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Jiayi Lei, Yao Fu, Maosong Sun, Junxian He:
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models. NeurIPS 2023 - [c30]Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, Michael Qizhe Xie:
Self-Evaluation Guided Beam Search for Reasoning. NeurIPS 2023 - [c29]Jinghan Zhang, Shiqi Chen, Junteng Liu, Junxian He:
Composing Parameter-Efficient Modules with Arithmetic Operation. NeurIPS 2023 - [i38]Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, Xu Zhao, Min-Yen Kan, Junxian He, Qizhe Xie:
Decomposition Enhances Reasoning via Self-Evaluation Guided Decoding. CoRR abs/2305.00633 (2023) - [i37]Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Jiayi Lei, Yao Fu, Maosong Sun, Junxian He:
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models. CoRR abs/2305.08322 (2023) - [i36]Shiqi Chen, Siyang Gao, Junxian He:
Evaluating Factual Consistency of Summaries with Large Language Models. CoRR abs/2305.14069 (2023) - [i35]Xu Zhao, Yuxi Xie, Kenji Kawaguchi, Junxian He, Qizhe Xie:
Automatic Model Selection with Large Language Models for Reasoning. CoRR abs/2305.14333 (2023) - [i34]Junlei Zhang, Zhenzhong Lan, Junxian He:
Contrastive Learning of Sentence Embeddings from Scratch. CoRR abs/2305.15077 (2023) - [i33]Cheng Deng, Tianhang Zhang, Zhongmou He, Qiyuan Chen, Yuanyuan Shi, Le Zhou, Luoyi Fu, Weinan Zhang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin, Junxian He:
Learning A Foundation Language Model for Geoscience Knowledge Understanding and Utilization. CoRR abs/2306.05064 (2023) - [i32]Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi:
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs. CoRR abs/2306.13063 (2023) - [i31]Jinghan Zhang, Shiqi Chen, Junteng Liu, Junxian He:
Composing Parameter-Efficient Modules with Arithmetic Operations. CoRR abs/2306.14870 (2023) - [i30]I-Chun Chern, Steffi Chern, Shiqi Chen, Weizhe Yuan, Kehua Feng, Chunting Zhou, Junxian He, Graham Neubig, Pengfei Liu:
FacTool: Factuality Detection in Generative AI - A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios. CoRR abs/2307.13528 (2023) - [i29]Keyu Duan, Qian Liu, Tat-Seng Chua, Shuicheng Yan, Wei Tsang Ooi, Qizhe Xie, Junxian He:
SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning. CoRR abs/2308.02565 (2023) - [i28]Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He:
FELM: Benchmarking Factuality Evaluation of Large Language Models. CoRR abs/2310.00741 (2023) - [i27]Qisheng Hu, Kaixin Li, Xu Zhao, Yuxi Xie, Tiedong Liu, Hui Chen, Qizhe Xie, Junxian He:
InstructCoder: Empowering Language Models for Code Editing. CoRR abs/2310.20329 (2023) - [i26]Xuan Long Do, Yiran Zhao, Hannah Brown, Yuxi Xie, James Xu Zhao, Nancy F. Chen, Kenji Kawaguchi, Michael Qizhe Xie, Junxian He:
Prompt Optimization via Adversarial In-Context Learning. CoRR abs/2312.02614 (2023) - [i25]Jiankai Sun, Chuanyang Zheng, Enze Xie, Zhengying Liu, Ruihang Chu, Jianing Qiu, Jiaqi Xu, Mingyu Ding, Hongyang Li, Mengzhe Geng, Yue Wu, Wenhai Wang, Junsong Chen, Zhangyue Yin, Xiaozhe Ren, Jie Fu, Junxian He, Wu Yuan, Qi Liu, Xihui Liu, Yu Li, Hao Dong, Yu Cheng, Ming Zhang, Pheng-Ann Heng, Jifeng Dai, Ping Luo, Jingdong Wang, Ji-Rong Wen, Xipeng Qiu, Yike Guo, Hui Xiong, Qun Liu, Zhenguo Li:
A Survey of Reasoning with Foundation Models. CoRR abs/2312.11562 (2023) - [i24]Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, Junxian He:
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning. CoRR abs/2312.15685 (2023) - 2022
- [j4]Haibing Wang, Zhen He, Tengxiao Wang, Junxian He, Xichuan Zhou, Ying Wang, Liyuan Liu, Nanjian Wu, Min Tian, Cong Shi:
TripleBrain: A Compact Neuromorphic Hardware Core With Fast On-Chip Self-Organizing and Reinforcement Spike-Timing Dependent Plasticity. IEEE Trans. Biomed. Circuits Syst. 16(4): 636-650 (2022) - [c28]Leyi Chen, Junxian He, Jianyi Yu, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Cong Shi, Min Tian:
An 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips. APCCAS 2022: 1-5 - [c27]Tengxiao Wang, Haibing Wang, Junxian He, Zhengqing Zhong, Fang Tang, Xichuan Zhou, Shuangming Yu, Liyuan Liu, Nanjian Wu, Min Tian, Cong Shi:
MorphBungee: An Edge Neuromorphic Chip for High-Accuracy On-Chip Learning of Multiple-Layer Spiking Neural Networks. BioCAS 2022: 255-259 - [c26]Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Prompt Consistency for Zero-Shot Task Generalization. EMNLP (Findings) 2022: 2613-2626 - [c25]Junxian He, Wojciech Kryscinski, Bryan McCann, Nazneen Rajani, Caiming Xiong:
CTRLsum: Towards Generic Controllable Text Summarization. EMNLP 2022: 5879-5915 - [c24]Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Towards a Unified View of Parameter-Efficient Transfer Learning. ICLR 2022 - [c23]Frank F. Xu, Junxian He, Graham Neubig, Vincent Josua Hellendoorn:
Capturing Structural Locality in Non-parametric Language Models. ICLR 2022 - [c22]Uri Alon, Frank F. Xu, Junxian He, Sudipta Sengupta, Dan Roth, Graham Neubig:
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval. ICML 2022: 468-485 - [c21]Cona Shi, Sihao Chen, Haibina Wana, Zhenaaina Zhona, Ping Li, Junxian He, Tengxiao Wang, Jianyi Yu, Min Tian:
TEDOP: A Tiny Event-Driven Neural Network Hardware Core Enabling On-Chip Spike-Driven Synaptic Plasticity. ICTA 2022: 62-63 - [i23]Uri Alon, Frank F. Xu, Junxian He, Sudipta Sengupta, Dan Roth, Graham Neubig:
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval. CoRR abs/2201.12431 (2022) - [i22]Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Prompt Consistency for Zero-Shot Task Generalization. CoRR abs/2205.00049 (2022) - [i21]Fatemehsadat Mireshghallah, Nikolai Vogler, Junxian He, Omar Florez, Ahmed El-Kishky, Taylor Berg-Kirkpatrick:
Non-Parametric Temporal Adaptation for Social Media Topic Classification. CoRR abs/2209.05706 (2022) - [i20]Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer:
Mega: Moving Average Equipped Gated Attention. CoRR abs/2209.10655 (2022) - 2021
- [j3]Tengxiao Wang, Cong Shi, Xichuan Zhou, Yingcheng Lin, Junxian He, Ping Gan, Ping Li, Ying Wang, Liyuan Liu, Nanjian Wu, Gang Luo:
CompSNN: A lightweight spiking neural network based on spatiotemporally compressive spike features. Neurocomputing 425: 96-106 (2021) - [j2]Cong Shi, Tengxiao Wang, Junxian He, Jianghao Zhang, Liyuan Liu, Nanjian Wu:
DeepTempo: A Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1581-1585 (2021) - [c20]Ruisi Su, Shruti Rijhwani, Hao Zhu, Junxian He, Xinyu Wang, Yonatan Bisk, Graham Neubig:
Dependency Induction Through the Lens of Visual Perception. CoNLL 2021: 17-26 - [c19]Jiajun Shen, Peng-Jen Chen, Matt Le, Junxian He, Jiatao Gu, Myle Ott, Michael Auli, Marc'Aurelio Ranzato:
The Source-Target Domain Mismatch Problem in Machine Translation. EACL 2021: 1519-1533 - [c18]Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick:
Efficient Nearest Neighbor Language Models. EMNLP (1) 2021: 5703-5714 - [c17]Yingcheng Lin, Rui Li, Wei He, Xichuan Zhou, Junxian He, Ping Li, Liyuan Liu, Nanjian Wu, Cong Shi:
A Pixel-Parallel Array Processor without Computational Logic for Computational Image Sensors. ICTA 2021: 51-52 - [c16]Haibing Wang, Zhen He, Jinsong Rao, Tengxiao Wang, Junxian He, Min Tian, Xichuan Zhou, Liyuan Liu, Nanjian Wu, Cong Shi:
TripleBrain: An Edge Neuromorphic Architecture for High-accuracy Single-layer Spiking Neural Network with On-chip Self-organizing and Reinforcement Learning. ICTA 2021: 88-89 - [i19]Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick:
Efficient Nearest Neighbor Language Models. CoRR abs/2109.04212 (2021) - [i18]Ruisi Su, Shruti Rijhwani, Hao Zhu, Junxian He, Xinyu Wang, Yonatan Bisk, Graham Neubig:
Dependency Induction Through the Lens of Visual Perception. CoRR abs/2109.09790 (2021) - [i17]Frank F. Xu, Junxian He, Graham Neubig, Vincent J. Hellendoorn:
Capturing Structural Locality in Non-parametric Language Models. CoRR abs/2110.02870 (2021) - [i16]Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Towards a Unified View of Parameter-Efficient Transfer Learning. CoRR abs/2110.04366 (2021) - 2020
- [j1]Wei He, Jinguo Huang, Tengxiao Wang, Yingcheng Lin, Junxian He, Xichuan Zhou, Ping Li, Ying Wang, Nanjian Wu, Cong Shi:
A High-Speed Low-Cost VLSI System Capable of On-Chip Online Learning for Dynamic Vision Sensor Data Classification. Sensors 20(17): 4715 (2020) - [c15]Bohan Li, Hao Zhou, Junxian He, Mingxuan Wang, Yiming Yang, Lei Li:
On the Sentence Embeddings from Pre-trained Language Models. EMNLP (1) 2020: 9119-9130 - [c14]Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato:
Revisiting Self-Training for Neural Sequence Generation. ICLR 2020 - [c13]Junxian He, Xinyi Wang, Graham Neubig, Taylor Berg-Kirkpatrick:
A Probabilistic Formulation of Unsupervised Text Style Transfer. ICLR 2020 - [c12]Yingcheng Lin, Rui Li, Wei He, Xichuan Zhou, Junxian He, Ping Li, Ying Jiang, Liyuan Liu, Nanjian Wu, Cong Shi:
A High-speed Low-cost CNN Inference Accelerator for Depthwise Separable Convolution. ICTA 2020: 63-64 - [c11]Junxian He, Taylor Berg-Kirkpatrick, Graham Neubig:
Learning Sparse Prototypes for Text Generation. NeurIPS 2020 - [i15]Junxian He, Xinyi Wang, Graham Neubig, Taylor Berg-Kirkpatrick:
A Probabilistic Formulation of Unsupervised Text Style Transfer. CoRR abs/2002.03912 (2020) - [i14]Junxian He, Taylor Berg-Kirkpatrick, Graham Neubig:
Learning Sparse Prototypes for Text Generation. CoRR abs/2006.16336 (2020) - [i13]Bohan Li, Hao Zhou, Junxian He, Mingxuan Wang, Yiming Yang, Lei Li:
On the Sentence Embeddings from Pre-trained Language Models. CoRR abs/2011.05864 (2020) - [i12]Junxian He, Wojciech Kryscinski, Bryan McCann, Nazneen Fatema Rajani, Caiming Xiong:
CTRLsum: Towards Generic Controllable Text Summarization. CoRR abs/2012.04281 (2020)
2010 – 2019
- 2019
- [c10]Zhiting Hu, Haoran Shi, Bowen Tan, Wentao Wang, Zichao Yang, Tiancheng Zhao, Junxian He, Lianhui Qin, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing:
Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. ACL (3) 2019: 159-164 - [c9]Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig:
Choosing Transfer Languages for Cross-Lingual Learning. ACL (1) 2019: 3125-3135 - [c8]Junxian He, Zhisong Zhang, Taylor Berg-Kirkpatrick, Graham Neubig:
Cross-Lingual Syntactic Transfer through Unsupervised Adaptation of Invertible Projections. ACL (1) 2019: 3211-3223 - [c7]Junxian He, Xichuan Zhou, Yingcheng Lin, Chonglei Sun, Cong Shi, Nanjian Wu, Gang Luo:
20, 000-fps Visual Motion Magnification on Pixel-parallel Vision Chip. ASICON 2019: 1-4 - [c6]Bohan Li, Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick, Yiming Yang:
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text. EMNLP/IJCNLP (1) 2019: 3601-3612 - [c5]Junxian He, Daniel Spokoyny, Graham Neubig, Taylor Berg-Kirkpatrick:
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders. ICLR (Poster) 2019 - [i11]Junxian He, Daniel Spokoyny, Graham Neubig, Taylor Berg-Kirkpatrick:
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders. CoRR abs/1901.05534 (2019) - [i10]Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig:
Choosing Transfer Languages for Cross-Lingual Learning. CoRR abs/1905.12688 (2019) - [i9]Junxian He, Zhisong Zhang, Taylor Berg-Kirkpatrick, Graham Neubig:
Cross-Lingual Syntactic Transfer through Unsupervised Adaptation of Invertible Projections. CoRR abs/1906.02656 (2019) - [i8]Bohan Li, Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick, Yiming Yang:
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text. CoRR abs/1909.00868 (2019) - [i7]Jiajun Shen, Peng-Jen Chen, Matt Le, Junxian He, Jiatao Gu, Myle Ott, Michael Auli, Marc'Aurelio Ranzato:
The Source-Target Domain Mismatch Problem in Machine Translation. CoRR abs/1909.13151 (2019) - [i6]Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato:
Revisiting Self-Training for Neural Sequence Generation. CoRR abs/1909.13788 (2019) - 2018
- [c4]Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig:
StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing. ACL (1) 2018: 754-765 - [c3]Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick:
Unsupervised Learning of Syntactic Structure with Invertible Neural Projections. EMNLP 2018: 1292-1302 - [i5]Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig:
StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing. CoRR abs/1806.07832 (2018) - [i4]Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick:
Unsupervised Learning of Syntactic Structure with Invertible Neural Projections. CoRR abs/1808.09111 (2018) - [i3]Zhiting Hu, Haoran Shi, Zichao Yang, Bowen Tan, Tiancheng Zhao, Junxian He, Wentao Wang, Xingjiang Yu, Lianhui Qin, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing:
Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. CoRR abs/1809.00794 (2018) - 2017
- [c2]Junxian He, Zhiting Hu, Taylor Berg-Kirkpatrick, Ying Huang, Eric P. Xing:
Efficient Correlated Topic Modeling with Topic Embedding. KDD 2017: 225-233 - [i2]Junxian He, Zhiting Hu, Taylor Berg-Kirkpatrick, Ying Huang, Eric P. Xing:
Efficient Correlated Topic Modeling with Topic Embedding. CoRR abs/1707.00206 (2017) - 2016
- [c1]Junxian He, Ying Huang, Changfeng Liu, Jiaming Shen, Yuting Jia, Xinbing Wang:
Text Network Exploration via Heterogeneous Web of Topics. ICDM Workshops 2016: 99-106 - [i1]Junxian He, Ying Huang, Changfeng Liu, Jiaming Shen, Yuting Jia, Xinbing Wang:
Text Network Exploration via Heterogeneous Web of Topics. CoRR abs/1610.00219 (2016)
Coauthor Index
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last updated on 2024-11-14 21:03 CET by the dblp team
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