A practical solution to wireless energy transfer in WSNs. - Zhenquan Qin; Chunting Zhou; Yue Yu; Lei Wang 005; Liang Sun 006; Yuanyuan Zhang (ICTC, 2013)

Optimized Periodical Charging in Large-Scale Deployed WSNs. - Zhenquan Qin; Bingxian Lu; Chunting Zhou; Lei Wang 005; Ming Zhu 001; Lei Shu 001; Xiaojing Zhu (GLOBECOM, 2015)

Efficient Methods for Multi-label Classification. - Chonglin Sun; Chunting Zhou; Bo Jin 001; Francis C. M. Lau 001 (PAKDD (1), 2015)

Category Enhanced Word Embedding. - Chunting Zhou; Chonglin Sun; Zhiyuan Liu 001; Francis C. M. Lau 001 (CoRR, 2015)

A C-LSTM Neural Network for Text Classification. - Chunting Zhou; Chonglin Sun; Zhiyuan Liu 001; Francis C. M. Lau 001 (CoRR, 2015)

Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction. - Chunting Zhou; Graham Neubig (ACL (1), 2017)

Morphological Inflection Generation with Multi-space Variational Encoder-Decoders. - Chunting Zhou; Graham Neubig (CoNLL Shared Task (1), 2017)

StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing. - Pengcheng Yin; Chunting Zhou; Junxian He; Graham Neubig (ACL (1), 2018)

Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations. - Aditi Chaudhary; Chunting Zhou; Lori S. Levin; Graham Neubig; David R. Mortensen; Jaime G. Carbonell (EMNLP, 2018)

FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow. - Xuezhe Ma; Chunting Zhou; Xian Li 003; Graham Neubig; Eduard H. Hovy (EMNLP/IJCNLP (1), 2019)

Handling Syntactic Divergence in Low-resource Machine Translation. - Chunting Zhou; Xuezhe Ma; Junjie Hu 001; Graham Neubig (EMNLP/IJCNLP (1), 2019)

MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders. - Xuezhe Ma; Chunting Zhou; Eduard H. Hovy (ICLR (Poster), 2019)

Density Matching for Bilingual Word Embedding. - Chunting Zhou; Xuezhe Ma; Di Wang 030; Graham Neubig (NAACL-HLT (1), 2019)

The ARIEL-CMU Systems for LoReHLT18. - Aditi Chaudhary; Siddharth Dalmia; Junjie Hu 001; Xinjian Li; Austin Matthews; Aldrian Obaja Muis; Naoki Otani; Shruti Rijhwani; Zaid Sheikh; Nidhi Vyas; Xinyi Wang 001; Jiateng Xie; et al. (CoRR, 2019)

Understanding Knowledge Distillation in Non-autoregressive Machine Translation. - Chunting Zhou; Jiatao Gu; Graham Neubig (ICLR, 2020)

Detecting Hallucinated Content in Conditional Neural Sequence Generation. - Chunting Zhou; Graham Neubig; Jiatao Gu; Mona T. Diab; Paco Guzman; Luke Zettlemoyer; Marjan Ghazvininejad (CoRR, 2020)

Detecting Hallucinated Content in Conditional Neural Sequence Generation. - Chunting Zhou; Graham Neubig; Jiatao Gu; Mona T. Diab; Francisco Guzmán; Luke Zettlemoyer; Marjan Ghazvininejad (ACL/IJCNLP (Findings), 2021)

Distributionally Robust Multilingual Machine Translation. - Chunting Zhou; Daniel Levy; Xian Li 003; Marjan Ghazvininejad; Graham Neubig (EMNLP (1), 2021)

Examining and Combating Spurious Features under Distribution Shift. - Chunting Zhou; Xuezhe Ma; Paul Michel; Graham Neubig (ICML, 2021)

Luna: Linear Unified Nested Attention. - Xuezhe Ma; Xiang Kong; Sinong Wang; Chunting Zhou; Jonathan May; Hao Ma 001; Luke Zettlemoyer (NeurIPS, 2021)

Learning Structures for Deep Neural Networks. - Jinhui Yuan; Fei Pan; Chunting Zhou; Tao Qin 001; Tie-Yan Liu (CoRR, 2021)

Prompt Consistency for Zero-Shot Task Generalization. - Chunting Zhou; Junxian He; Xuezhe Ma; Taylor Berg-Kirkpatrick; Graham Neubig (EMNLP (Findings), 2022)

Towards a Unified View of Parameter-Efficient Transfer Learning. - Junxian He; Chunting Zhou; Xuezhe Ma; Taylor Berg-Kirkpatrick; Graham Neubig (ICLR, 2022)

In-context Examples Selection for Machine Translation. - Sweta Agrawal; Chunting Zhou; Mike Lewis; Luke Zettlemoyer; Marjan Ghazvininejad (ACL (Findings), 2023)

Multi-Dimensional Evaluation of Text Summarization with In-Context Learning. - Sameer Jain; Vaishakh Keshava; Swarnashree Mysore Sathyendra; Patrick Fernandes; Pengfei Liu 003; Graham Neubig; Chunting Zhou (ACL (Findings), 2023)

Training Trajectories of Language Models Across Scales. - Mengzhou Xia; Mikel Artetxe; Chunting Zhou; Xi Victoria Lin; Ramakanth Pasunuru; Danqi Chen 001; Luke Zettlemoyer; Veselin Stoyanov (ACL (1), 2023)

Look-back Decoding for Open-Ended Text Generation. - Nan Xu; Chunting Zhou; Asli Celikyilmaz; Xuezhe Ma (EMNLP, 2023)

Mega: Moving Average Equipped Gated Attention. - Xuezhe Ma; Chunting Zhou; Xiang Kong; Junxian He; Liangke Gui; Graham Neubig; Jonathan May; Luke Zettlemoyer (ICLR, 2023)

LIMA: Less Is More for Alignment. - Chunting Zhou; Pengfei Liu; Puxin Xu; Srinivasan Iyer 001; Jiao Sun; Yuning Mao; Xuezhe Ma; Avia Efrat; Ping Yu; Lili Yu; Susan Zhang; Gargi Ghosh; et al. (NeurIPS, 2023)

FacTool: Factuality Detection in Generative AI - A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios. - I-Chun Chern; Steffi Chern; Shiqi Chen; Weizhe Yuan; Kehua Feng; Chunting Zhou; Junxian He; Graham Neubig; Pengfei Liu 003 (CoRR, 2023)

Mitigating Semantic and Distributional Discrepancies in Natural Language Processing - Chunting Zhou (2023)

Instruction-tuned Language Models are Better Knowledge Learners. - Zhengbao Jiang; Zhiqing Sun; Weijia Shi; Pedro Rodríguez 001; Chunting Zhou; Graham Neubig; Xi Victoria Lin; Wen-tau Yih; Srini Iyer 001 (ACL (1), 2024)

Self-Alignment with Instruction Backtranslation. - Xian Li 003; Ping Yu; Chunting Zhou; Timo Schick; Omer Levy; Luke Zettlemoyer; Jason Weston; Mike Lewis (ICLR, 2024)

In-Context Pretraining: Language Modeling Beyond Document Boundaries. - Weijia Shi; Sewon Min; Maria Lomeli; Chunting Zhou; Margaret Li; Xi Victoria Lin; Noah A. Smith; Luke Zettlemoyer; Wen-tau Yih; Mike Lewis (ICLR, 2024)

MART: Improving LLM Safety with Multi-round Automatic Red-Teaming. - Suyu Ge; Chunting Zhou; Rui Hou; Madian Khabsa; Yi-Chia Wang; Qifan Wang 001; Jiawei Han 001; Yuning Mao (NAACL-HLT, 2024)

Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length. - Xuezhe Ma; Xiaomeng Yang; Wenhan Xiong; Beidi Chen; Lili Yu; Hao Zhang 025; Jonathan May; Luke Zettlemoyer; Omer Levy; Chunting Zhou (NeurIPS, 2024)

ALMA: Alignment with Minimal Annotation. - Michihiro Yasunaga; Leonid Shamis; Chunting Zhou; Andrew Cohen; Jason Weston; Luke Zettlemoyer; Marjan Ghazvininejad (CoRR, 2024)

LMFusion: Adapting Pretrained Language Models for Multimodal Generation. - Weijia Shi; Xiaochuang Han; Chunting Zhou; Weixin Liang; Xi Victoria Lin; Luke Zettlemoyer; Lili Yu (CoRR, 2024)

Byte Latent Transformer: Patches Scale Better Than Tokens. - Artidoro Pagnoni; Ramakanth Pasunuru; Pedro Rodríguez 001; John Nguyen; Benjamin Muller; Margaret Li; Chunting Zhou; Lili Yu; Jason E. Weston; Luke Zettlemoyer; Gargi Ghosh; Mike Lewis; et al. (ACL (1), 2025)

Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model. - Chunting Zhou; Lili Yu; Arun Babu; Kushal Tirumala; Michihiro Yasunaga; Leonid Shamis; Jacob Kahn; Xuezhe Ma; Luke Zettlemoyer; Omer Levy (ICLR, 2025)

Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models. - Weixin Liang; Lili Yu; Liang Luo; Srini Iyer 001; Ning Dong; Chunting Zhou; Gargi Ghosh; Mike Lewis; Wen-tau Yih; Luke Zettlemoyer; Xi Victoria Lin (Trans. Mach. Learn. Res., 2025)

CAT: Content-Adaptive Image Tokenization. - Junhong Shen; Kushal Tirumala; Michihiro Yasunaga; Ishan Misra; Luke Zettlemoyer; Lili Yu; Chunting Zhou (CoRR, 2025)