Search Results for author: Wanyu Du

Found 11 papers, 7 papers with code

Improving Iterative Text Revision by Learning Where to Edit from Other Revision Tasks

1 code implementation2 Dec 2022 Zae Myung Kim, Wanyu Du, Vipul Raheja, Dhruv Kumar, Dongyeop Kang

Leveraging datasets from other related text editing NLP tasks, combined with the specification of editable spans, leads our system to more accurately model the process of iterative text refinement, as evidenced by empirical results and human evaluations.

Grammatical Error Correction Sentence Fusion +2

Self-training with Two-phase Self-augmentation for Few-shot Dialogue Generation

1 code implementation19 May 2022 Wanyu Du, Hanjie Chen, Yangfeng Ji

In task-oriented dialogue systems, response generation from meaning representations (MRs) often suffers from limited training examples, due to the high cost of annotating MR-to-Text pairs.

Dialogue Generation Language Modelling +2

Read, Revise, Repeat: A System Demonstration for Human-in-the-loop Iterative Text Revision

1 code implementation In2Writing (ACL) 2022 Wanyu Du, Zae Myung Kim, Vipul Raheja, Dhruv Kumar, Dongyeop Kang

Examining and evaluating the capability of large language models for making continuous revisions and collaborating with human writers is a critical step towards building effective writing assistants.

Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors

1 code implementation4 Apr 2022 Wanyu Du, Jianqiao Zhao, LiWei Wang, Yangfeng Ji

The proposed stochastic function is sampled from a Gaussian process prior to (1) provide infinite number of joint Gaussian distributions of random context variables (diversity-promoting) and (2) explicitly model dependency between context variables (accurate-encoding).

Gaussian Processes Paraphrase Generation +4

FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows

no code implementations14 Feb 2022 Jianqiao Zhao, Yanyang Li, Wanyu Du, Yangfeng Ji, Dong Yu, Michael R. Lyu, LiWei Wang

Hence, we propose segment act, an extension of dialog act from utterance level to segment level, and crowdsource a large-scale dataset for it.

Dialogue Evaluation

Explaining Predictive Uncertainty by Looking Back at Model Explanations

no code implementations11 Jan 2022 Hanjie Chen, Wanyu Du, Yangfeng Ji

Explaining predictive uncertainty is an important complement to explaining prediction labels in helping users understand model decision making and gaining their trust on model predictions, while has been largely ignored in prior works.

Decision Making Natural Language Inference +2

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