Search Results for author: Chunting Zhou

Found 19 papers, 12 papers with code

Prompt Consistency for Zero-Shot Task Generalization

1 code implementation29 Apr 2022 Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig

One of the most impressive results of recent NLP history is the ability of pre-trained language models to solve new tasks in a zero-shot setting.

Towards a Unified View of Parameter-Efficient Transfer Learning

1 code implementation ICLR 2022 Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig

Furthermore, our unified framework enables the transfer of design elements across different approaches, and as a result we are able to instantiate new parameter-efficient fine-tuning methods that tune less parameters than previous methods while being more effective, achieving comparable results to fine-tuning all parameters on all four tasks.

Machine Translation Text Classification +2

Distributionally Robust Multilingual Machine Translation

1 code implementation EMNLP 2021 Chunting Zhou, Daniel Levy, Xian Li, Marjan Ghazvininejad, Graham Neubig

Multilingual neural machine translation (MNMT) learns to translate multiple language pairs with a single model, potentially improving both the accuracy and the memory-efficiency of deployed models.

Machine Translation Translation

Examining and Combating Spurious Features under Distribution Shift

1 code implementation14 Jun 2021 Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig

Group distributionally robust optimization (DRO) provides an effective tool to alleviate covariate shift by minimizing the worst-case training loss over a set of pre-defined groups.

Learning Structures for Deep Neural Networks

no code implementations27 May 2021 Jinhui Yuan, Fei Pan, Chunting Zhou, Tao Qin, Tie-Yan Liu

We further establish connections between this principle and the theory of Bayesian optimal classification, and empirically verify that larger entropy of the outputs of a deep neural network indeed corresponds to a better classification accuracy.

Classification Image Classification

Detecting Hallucinated Content in Conditional Neural Sequence Generation

1 code implementation Findings (ACL) 2021 Chunting Zhou, Graham Neubig, Jiatao Gu, Mona Diab, Paco Guzman, Luke Zettlemoyer, Marjan Ghazvininejad

Neural sequence models can generate highly fluent sentences, but recent studies have also shown that they are also prone to hallucinate additional content not supported by the input.

Abstractive Text Summarization Machine Translation +1

Understanding Knowledge Distillation in Non-autoregressive Machine Translation

no code implementations ICLR 2020 Chunting Zhou, Graham Neubig, Jiatao Gu

We find that knowledge distillation can reduce the complexity of data sets and help NAT to model the variations in the output data.

Knowledge Distillation Machine Translation +1

Handling Syntactic Divergence in Low-resource Machine Translation

1 code implementation IJCNLP 2019 Chunting Zhou, Xuezhe Ma, Junjie Hu, Graham Neubig

Despite impressive empirical successes of neural machine translation (NMT) on standard benchmarks, limited parallel data impedes the application of NMT models to many language pairs.

Data Augmentation Machine Translation +1

Density Matching for Bilingual Word Embedding

1 code implementation NAACL 2019 Chunting Zhou, Xuezhe Ma, Di Wang, Graham Neubig

Recent approaches to cross-lingual word embedding have generally been based on linear transformations between the sets of embedding vectors in the two languages.

Bilingual Lexicon Induction Word Embeddings +1

The ARIEL-CMU Systems for LoReHLT18

no code implementations24 Feb 2019 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 Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard Hovy, Alan W. black, Jaime Carbonell, Graham V. Horwood, Shabnam Tafreshi, Mona Diab, Efsun S. Kayi, Noura Farra, Kathleen McKeown

This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).

Machine Translation Translation

MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders

no code implementations ICLR 2019 Xuezhe Ma, Chunting Zhou, Eduard Hovy

Variational Autoencoder (VAE), a simple and effective deep generative model, has led to a number of impressive empirical successes and spawned many advanced variants and theoretical investigations.

Density Estimation Image Generation +1

StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing

6 code implementations ACL 2018 Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig

Semantic parsing is the task of transducing natural language (NL) utterances into formal meaning representations (MRs), commonly represented as tree structures.

Code Generation Semantic Parsing

Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction

no code implementations ACL 2017 Chunting Zhou, Graham Neubig

Labeled sequence transduction is a task of transforming one sequence into another sequence that satisfies desiderata specified by a set of labels.

Morphological Inflection

Category Enhanced Word Embedding

no code implementations27 Nov 2015 Chunting Zhou, Chonglin Sun, Zhiyuan Liu, Francis C. M. Lau

In this paper, we incorporate category information of documents in the learning of word representations and to learn the proposed models in a document-wise manner.

General Classification Representation Learning +3

A C-LSTM Neural Network for Text Classification

10 code implementations27 Nov 2015 Chunting Zhou, Chonglin Sun, Zhiyuan Liu, Francis C. M. Lau

In this work, we combine the strengths of both architectures and propose a novel and unified model called C-LSTM for sentence representation and text classification.

Classification General Classification +2

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