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2020 – today
- 2024
[c28]Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodríguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srini Iyer:
Instruction-tuned Language Models are Better Knowledge Learners. ACL (1) 2024: 5421-5434- [c27]Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason Weston, Mike Lewis:
Self-Alignment with Instruction Backtranslation. ICLR 2024 - [c26]Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Wen-tau Yih, Mike Lewis:
In-Context Pretraining: Language Modeling Beyond Document Boundaries. ICLR 2024 - [c25]Suyu Ge, Chunting Zhou, Rui Hou, Madian Khabsa, Yi-Chia Wang, Qifan Wang, Jiawei Han, Yuning Mao:
MART: Improving LLM Safety with Multi-round Automatic Red-Teaming. NAACL-HLT 2024: 1927-1937 - [i31]Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodriguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srinivasan Iyer:
Instruction-tuned Language Models are Better Knowledge Learners. CoRR abs/2402.12847 (2024) - [i30]Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou:
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length. CoRR abs/2404.08801 (2024) - [i29]Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, Omer Levy:
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model. CoRR abs/2408.11039 (2024) - 2023
- [c24]Sameer Jain, Vaishakh Keshava, Swarnashree Mysore Sathyendra, Patrick Fernandes, Pengfei Liu, Graham Neubig, Chunting Zhou:
Multi-Dimensional Evaluation of Text Summarization with In-Context Learning. ACL (Findings) 2023: 8487-8495 - [c23]Sweta Agrawal, Chunting Zhou, Mike Lewis, Luke Zettlemoyer, Marjan Ghazvininejad:
In-context Examples Selection for Machine Translation. ACL (Findings) 2023: 8857-8873 - [c22]Mengzhou Xia, Mikel Artetxe, Chunting Zhou, Xi Victoria Lin, Ramakanth Pasunuru, Danqi Chen, Luke Zettlemoyer, Veselin Stoyanov:
Training Trajectories of Language Models Across Scales. ACL (1) 2023: 13711-13738 - [c21]Nan Xu, Chunting Zhou, Asli Celikyilmaz, Xuezhe Ma:
Look-back Decoding for Open-Ended Text Generation. EMNLP 2023: 1039-1050 - [c20]Xuezhe Ma
, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer:
Mega: Moving Average Equipped Gated Attention. ICLR 2023 - [c19]Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. NeurIPS 2023 - [i28]Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. CoRR abs/2305.11206 (2023) - [i27]Nan Xu, Chunting Zhou, Asli Celikyilmaz, Xuezhe Ma:
Look-back Decoding for Open-Ended Text Generation. CoRR abs/2305.13477 (2023) - [i26]Sameer Jain, Vaishakh Keshava, Swarnashree Mysore Sathyendra, Patrick Fernandes, Pengfei Liu, Graham Neubig, Chunting Zhou:
Multi-Dimensional Evaluation of Text Summarization with In-Context Learning. CoRR abs/2306.01200 (2023) - [i25]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) - [i24]Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, Mike Lewis:
Self-Alignment with Instruction Backtranslation. CoRR abs/2308.06259 (2023) - [i23]Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis:
In-Context Pretraining: Language Modeling Beyond Document Boundaries. CoRR abs/2310.10638 (2023) - [i22]Suyu Ge, Chunting Zhou, Rui Hou, Madian Khabsa, Yi-Chia Wang, Qifan Wang, Jiawei Han, Yuning Mao:
MART: Improving LLM Safety with Multi-round Automatic Red-Teaming. CoRR abs/2311.07689 (2023) - 2022
- [c18]Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Prompt Consistency for Zero-Shot Task Generalization. EMNLP (Findings) 2022: 2613-2626 - [c17]Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Towards a Unified View of Parameter-Efficient Transfer Learning. ICLR 2022 - [e1]Alon Albalak, Chunting Zhou, Colin Raffel, Deepak Ramachandran, Sebastian Ruder, Xuezhe Ma:
Transfer Learning for Natural Language Processing Workshop, 03 December 2022, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 203, PMLR 2022 [contents] - [i21]Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig:
Prompt Consistency for Zero-Shot Task Generalization. CoRR abs/2205.00049 (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) - [i19]Sweta Agrawal, Chunting Zhou, Mike Lewis, Luke Zettlemoyer, Marjan Ghazvininejad:
In-context Examples Selection for Machine Translation. CoRR abs/2212.02437 (2022) - [i18]Mengzhou Xia, Mikel Artetxe, Chunting Zhou, Xi Victoria Lin, Ramakanth Pasunuru, Danqi Chen, Luke Zettlemoyer, Ves Stoyanov:
Training Trajectories of Language Models Across Scales. CoRR abs/2212.09803 (2022) - 2021
- [c16]Chunting Zhou, Graham Neubig, Jiatao Gu, Mona T. Diab, Francisco Guzmán, Luke Zettlemoyer, Marjan Ghazvininejad:
Detecting Hallucinated Content in Conditional Neural Sequence Generation. ACL/IJCNLP (Findings) 2021: 1393-1404 - [c15]Chunting Zhou, Daniel Levy, Xian Li, Marjan Ghazvininejad, Graham Neubig:
Distributionally Robust Multilingual Machine Translation. EMNLP (1) 2021: 5664-5674 - [c14]Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig:
Examining and Combating Spurious Features under Distribution Shift. ICML 2021: 12857-12867 - [c13]Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer:
Luna: Linear Unified Nested Attention. NeurIPS 2021: 2441-2453 - [i17]Jinhui Yuan, Fei Pan, Chunting Zhou, Tao Qin, Tie-Yan Liu:
Learning Structures for Deep Neural Networks. CoRR abs/2105.13905 (2021) - [i16]Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer:
Luna: Linear Unified Nested Attention. CoRR abs/2106.01540 (2021) - [i15]Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig:
Examining and Combating Spurious Features under Distribution Shift. CoRR abs/2106.07171 (2021) - [i14]Chunting Zhou, Daniel Levy, Xian Li, Marjan Ghazvininejad, Graham Neubig:
Distributionally Robust Multilingual Machine Translation. CoRR abs/2109.04020 (2021) - [i13]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
- [c12]Chunting Zhou, Jiatao Gu, Graham Neubig:
Understanding Knowledge Distillation in Non-autoregressive Machine Translation. ICLR 2020 - [i12]Chunting Zhou, Jiatao Gu, Mona T. Diab, Paco Guzman, Luke Zettlemoyer, Marjan Ghazvininejad:
Detecting Hallucinated Content in Conditional Neural Sequence Generation. CoRR abs/2011.02593 (2020)
2010 – 2019
- 2019
- [c11]Chunting Zhou, Xuezhe Ma, Junjie Hu, Graham Neubig:
Handling Syntactic Divergence in Low-resource Machine Translation. EMNLP/IJCNLP (1) 2019: 1388-1394 - [c10]Xuezhe Ma, Chunting Zhou, Xian Li, Graham Neubig, Eduard H. Hovy:
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow. EMNLP/IJCNLP (1) 2019: 4281-4291 - [c9]Xuezhe Ma, Chunting Zhou, Eduard H. Hovy:
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders. ICLR (Poster) 2019 - [c8]Chunting Zhou, Xuezhe Ma, Di Wang, Graham Neubig:
Density Matching for Bilingual Word Embedding. NAACL-HLT (1) 2019: 1588-1598 - [i11]Xuezhe Ma, Chunting Zhou, Eduard H. Hovy:
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders. CoRR abs/1901.01498 (2019) - [i10]Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori S. Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard H. Hovy, Alan W. Black, Jaime G. Carbonell, Graham Horwood, Shabnam Tafreshi, Mona T. Diab, Efsun Sarioglu Kayi, Noura Farra, Kathleen R. McKeown:
The ARIEL-CMU Systems for LoReHLT18. CoRR abs/1902.08899 (2019) - [i9]Chunting Zhou, Xuezhe Ma, Di Wang, Graham Neubig:
Density Matching for Bilingual Word Embedding. CoRR abs/1904.02343 (2019) - [i8]Chunting Zhou, Xuezhe Ma, Junjie Hu, Graham Neubig:
Handling Syntactic Divergence in Low-resource Machine Translation. CoRR abs/1909.00040 (2019) - [i7]Xuezhe Ma, Chunting Zhou, Xian Li, Graham Neubig, Eduard H. Hovy:
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow. CoRR abs/1909.02480 (2019) - [i6]Chunting Zhou, Graham Neubig, Jiatao Gu:
Understanding Knowledge Distillation in Non-autoregressive Machine Translation. CoRR abs/1911.02727 (2019) - 2018
- [c7]Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig:
StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing. ACL (1) 2018: 754-765 - [c6]Aditi Chaudhary, Chunting Zhou, Lori S. Levin, Graham Neubig, David R. Mortensen, Jaime G. Carbonell:
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations. EMNLP 2018: 3285-3295 - [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]Aditi Chaudhary, Chunting Zhou, Lori S. Levin, Graham Neubig, David R. Mortensen, Jaime G. Carbonell:
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations. CoRR abs/1808.09500 (2018) - 2017
- [c5]Chunting Zhou, Graham Neubig:
Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction. ACL (1) 2017: 310-320 - [c4]Chunting Zhou, Graham Neubig:
Morphological Inflection Generation with Multi-space Variational Encoder-Decoders. CoNLL Shared Task (1) 2017: 58-65 - [i3]Chunting Zhou, Graham Neubig:
Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction. CoRR abs/1704.01691 (2017) - 2015
- [c3]Zhenquan Qin, Bingxian Lu, Chunting Zhou, Lei Wang, Ming Zhu, Lei Shu, Xiaojing Zhu:
Optimized Periodical Charging in Large-Scale Deployed WSNs. GLOBECOM 2015: 1-6 - [c2]Chonglin Sun, Chunting Zhou, Bo Jin, Francis C. M. Lau:
Efficient Methods for Multi-label Classification. PAKDD (1) 2015: 164-175 - [i2]Chunting Zhou, Chonglin Sun, Zhiyuan Liu, Francis C. M. Lau:
Category Enhanced Word Embedding. CoRR abs/1511.08629 (2015) - [i1]Chunting Zhou, Chonglin Sun, Zhiyuan Liu, Francis C. M. Lau:
A C-LSTM Neural Network for Text Classification. CoRR abs/1511.08630 (2015) - 2013
- [c1]Zhenquan Qin, Chunting Zhou, Yue Yu, Lei Wang, Liang Sun, Yuanyuan Zhang:
A practical solution to wireless energy transfer in WSNs. ICTC 2013: 660-665
Coauthor Index
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