Search Results for author: Piji Li

Found 45 papers, 22 papers with code

COSPLAY: Concept Set Guided Personalized Dialogue Generation Across Both Party Personas

1 code implementation2 May 2022 Chen Xu, Piji Li, Wei Wang, Haoran Yang, Siyun Wang, Chuangbai Xiao

In this work, we propose COSPLAY(COncept Set guided PersonaLized dialogue generation Across both partY personas) that considers both parties as a "team": expressing self-persona while keeping curiosity toward the partner, leading responses around mutual personas, and finding the common ground.

Dialogue Generation

Event Transition Planning for Open-ended Text Generation

no code implementations Findings (ACL) 2022 Qintong Li, Piji Li, Wei Bi, Zhaochun Ren, Yuxuan Lai, Lingpeng Kong

Open-ended text generation tasks, such as dialogue generation and story completion, require models to generate a coherent continuation given limited preceding context.

Dialogue Generation Story Completion

Parameter-Efficient Tuning by Manipulating Hidden States of Pretrained Language Models For Classification Tasks

no code implementations10 Apr 2022 Haoran Yang, Piji Li, Wai Lam

Continuous prompt tuning which prepends a few trainable vectors to the embeddings of input is one of these methods and has drawn much attention due to its effectiveness and efficiency.

Pretrained Language Models

Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation

1 code implementation Findings (EMNLP) 2021 Haoran Yang, Wai Lam, Piji Li

Exemplar-Guided Paraphrase Generation (EGPG) aims to generate a target sentence which conforms to the style of the given exemplar while encapsulating the content information of the source sentence.

Contrastive Learning Paraphrase Generation +2

Sentence Semantic Regression for Text Generation

no code implementations6 Aug 2021 Wei Wang, Piji Li, Hai-Tao Zheng

In the phase of surface realization, a mixed-granularity sentence decoder is designed to generate text with better consistency by jointly incorporating the predicted sentence-level main idea as well as the preceding contextual token-level information.

Dialogue Generation Language Modelling

Dialogue Summarization with Supporting Utterance Flow Modeling and Fact Regularization

1 code implementation3 Aug 2021 Wang Chen, Piji Li, Hou Pong Chan, Irwin King

The supporting utterance flow modeling helps to generate a coherent summary by smoothly shifting the focus from the former utterances to the later ones.

CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding

1 code implementation ACL 2021 Dong Wang, Ning Ding, Piji Li, Hai-Tao Zheng

Recent works aimed to improve the robustness of pre-trained models mainly focus on adversarial training from perturbed examples with similar semantics, neglecting the utilization of different or even opposite semantics.

Contrastive Learning Natural Language Understanding +2

Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction

1 code implementation ACL 2021 Piji Li, Shuming Shi

We investigate the problem of Chinese Grammatical Error Correction (CGEC) and present a new framework named Tail-to-Tail (\textbf{TtT}) non-autoregressive sequence prediction to address the deep issues hidden in CGEC.

Grammatical Error Correction

Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection

no code implementations13 Feb 2021 Wei Wang, Piji Li, Hai-Tao Zheng

Automatic comment generation is a special and challenging task to verify the model ability on news content comprehension and language generation.

Saliency Detection Text Generation

Abstractive Opinion Tagging

1 code implementation18 Jan 2021 Qintong Li, Piji Li, Xinyi Li, Zhaochun Ren, Zhumin Chen, Maarten de Rijke

In this paper, we propose the abstractive opinion tagging task, where systems have to automatically generate a ranked list of opinion tags that are based on, but need not occur in, a given set of user-generated reviews.

Predicting Events in MOBA Games: Prediction, Attribution, and Evaluation

no code implementations17 Dec 2020 Zelong Yang, Yan Wang, Piji Li, Shaobin Lin, Shuming Shi, Shao-Lun Huang, Wei Bi

The multiplayer online battle arena (MOBA) games have become increasingly popular in recent years.

Consistency and Coherency Enhanced Story Generation

no code implementations17 Oct 2020 Wei Wang, Piji Li, Hai-Tao Zheng

In terms of consistency, on one hand, GPT2 cannot guarantee the consistency of the plots explicitly.

Language Modelling Story Generation

Knowledge Bridging for Empathetic Dialogue Generation

1 code implementation21 Sep 2020 Qintong Li, Piji Li, Zhaochun Ren, Pengjie Ren, Zhumin Chen

Finally, to generate the empathetic response, we propose an emotional cross-attention mechanism to learn the emotional dependencies from the emotional context graph.

Dialogue Generation

Enhancing Dialogue Generation via Multi-Level Contrastive Learning

no code implementations19 Sep 2020 Xin Li, Piji Li, Yan Wang, Xiaojiang Liu, Wai Lam

Most of the existing works for dialogue generation are data-driven models trained directly on corpora crawled from websites.

Contrastive Learning Dialogue Generation

Exclusive Hierarchical Decoding for Deep Keyphrase Generation

1 code implementation ACL 2020 Wang Chen, Hou Pong Chan, Piji Li, Irwin King

A new setting is recently introduced into this problem, in which, given a document, the model needs to predict a set of keyphrases and simultaneously determine the appropriate number of keyphrases to produce.

Keyphrase Generation

Salience Estimation with Multi-Attention Learning for Abstractive Text Summarization

no code implementations7 Apr 2020 Piji Li, Lidong Bing, Zhongyu Wei, Wai Lam

Different from neural machine translation, in the task of text summarization, salience estimation for words, phrases or sentences is a critical component, since the output summary is a distillation of the input text.

Abstractive Text Summarization Machine Translation +1

An Empirical Investigation of Pre-Trained Transformer Language Models for Open-Domain Dialogue Generation

1 code implementation9 Mar 2020 Piji Li

A weighted joint prediction paradigm for both context and response is designed to evaluate the performance of models with or without the loss term for context prediction.

Dialogue Generation

A Neural Topical Expansion Framework for Unstructured Persona-oriented Dialogue Generation

2 code implementations6 Feb 2020 Minghong Xu, Piji Li, Haoran Yang, Pengjie Ren, Zhaochun Ren, Zhumin Chen, Jun Ma

To address this, we propose a neural topical expansion framework, namely Persona Exploration and Exploitation (PEE), which is able to extend the predefined user persona description with semantically correlated content before utilizing them to generate dialogue responses.

Dialogue Generation

Relevance-Promoting Language Model for Short-Text Conversation

no code implementations26 Nov 2019 Xin Li, Piji Li, Wei Bi, Xiaojiang Liu, Wai Lam

In this paper, we propose to formulate the STC task as a language modeling problem and tailor-make a training strategy to adapt a language model for response generation.

Language Modelling Response Generation +1

Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion

no code implementations IJCNLP 2019 Zihao Wang, Kwun Ping Lai, Piji Li, Lidong Bing, Wai Lam

Therefore, we propose a meta-learning framework that aims at handling infrequent relations with few-shot learning and uncommon entities by using textual descriptions.

Few-Shot Learning Knowledge Graph Completion

Semi-supervised Text Style Transfer: Cross Projection in Latent Space

no code implementations IJCNLP 2019 Mingyue Shang, Piji Li, Zhenxin Fu, Lidong Bing, Dongyan Zhao, Shuming Shi, Rui Yan

Text style transfer task requires the model to transfer a sentence of one style to another style while retaining its original content meaning, which is a challenging problem that has long suffered from the shortage of parallel data.

Style Transfer Text Style Transfer

How to Write Summaries with Patterns? Learning towards Abstractive Summarization through Prototype Editing

1 code implementation IJCNLP 2019 Shen Gao, Xiuying Chen, Piji Li, Zhangming Chan, Dongyan Zhao, Rui Yan

There are two main challenges in this task: (1) the model needs to incorporate learned patterns from the prototype, but (2) should avoid copying contents other than the patternized words---such as irrelevant facts---into the generated summaries.

Abstractive Text Summarization

Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling

1 code implementation ACL 2019 Yifan Gao, Piji Li, Irwin King, Michael R. Lyu

The coreference alignment modeling explicitly aligns coreferent mentions in conversation history with corresponding pronominal references in generated questions, which makes generated questions interconnected to conversation history.

Question Answering Question Generation

An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extraction

1 code implementation NAACL 2019 Wang Chen, Hou Pong Chan, Piji Li, Lidong Bing, Irwin King

For further exploiting the power of extraction and retrieval, we propose a neural-based merging module to combine and re-rank the predicted keyphrases from the enhanced generative model, the extractive model, and the retrieved keyphrases.

Keyphrase Generation Multi-Task Learning

Persona-Aware Tips Generation

no code implementations6 Mar 2019 Piji Li, ZiHao Wang, Lidong Bing, Wai Lam

In order to exploit the persona information, we propose a framework based on adversarial variational auto-encoders (aVAE) for persona modeling from the historical tips and reviews of users and items.

Abstractive Text Summarization by Incorporating Reader Comments

no code implementations13 Dec 2018 Shen Gao, Xiuying Chen, Piji Li, Zhaochun Ren, Lidong Bing, Dongyan Zhao, Rui Yan

To tackle this problem, we propose the task of reader-aware abstractive summary generation, which utilizes the reader comments to help the model produce better summary about the main aspect.

Reader-Aware Summarization

Generating Distractors for Reading Comprehension Questions from Real Examinations

2 code implementations8 Sep 2018 Yifan Gao, Lidong Bing, Piji Li, Irwin King, Michael R. Lyu

We investigate the task of distractor generation for multiple choice reading comprehension questions from examinations.

Distractor Generation Multiple-choice +1

Aspect Term Extraction with History Attention and Selective Transformation

1 code implementation2 May 2018 Xin Li, Lidong Bing, Piji Li, Wai Lam, Zhimou Yang

Aspect Term Extraction (ATE), a key sub-task in Aspect-Based Sentiment Analysis, aims to extract explicit aspect expressions from online user reviews.

Aspect-Based Sentiment Analysis Term Extraction

Actor-Critic based Training Framework for Abstractive Summarization

no code implementations28 Mar 2018 Piji Li, Lidong Bing, Wai Lam

For the critic, we combine the maximum likelihood estimator with a well designed global summary quality estimator which is a neural network based binary classifier aiming to make the generated summaries indistinguishable from the human-written ones.

Abstractive Text Summarization

Deep Recurrent Generative Decoder for Abstractive Text Summarization

1 code implementation EMNLP 2017 Piji Li, Wai Lam, Lidong Bing, ZiHao Wang

We propose a new framework for abstractive text summarization based on a sequence-to-sequence oriented encoder-decoder model equipped with a deep recurrent generative decoder (DRGN).

Abstractive Text Summarization Variational Inference

Neural Rating Regression with Abstractive Tips Generation for Recommendation

no code implementations1 Aug 2017 Piji Li, ZiHao Wang, Zhaochun Ren, Lidong Bing, Wai Lam

In essence, writing some tips and giving a numerical rating are two facets of a user's product assessment action, expressing the user experience and feelings.

Abstractive Multi-Document Summarization via Phrase Selection and Merging

no code implementations IJCNLP 2015 Lidong Bing, Piji Li, Yi Liao, Wai Lam, Weiwei Guo, Rebecca J. Passonneau

We propose an abstraction-based multi-document summarization framework that can construct new sentences by exploring more fine-grained syntactic units than sentences, namely, noun/verb phrases.

Document Summarization Multi-Document Summarization

Cannot find the paper you are looking for? You can Submit a new open access paper.