no code implementations • NAACL 2022 • Hongyuan Lu, Wai Lam, Hong Cheng, Helen Meng
Incorporating personas information allows diverse and engaging responses in dialogue response generation.
no code implementations • RANLP 2021 • Xin Shen, Wai Lam
Our method forces the network to learn the necessary features for all the words in the input, which alleviates the shortcut learning problem.
1 code implementation • ACL 2022 • Chun Hei Lo, Wai Lam, Hong Cheng
We introduce a data-driven approach to generating derivation trees from meaning representation graphs with probabilistic synchronous hyperedge replacement grammar (PSHRG).
no code implementations • EMNLP 2020 • Wenxuan Zhang, Yang Deng, Jing Ma, Wai Lam
Product-related question answering platforms nowadays are widely employed in many E-commerce sites, providing a convenient way for potential customers to address their concerns during online shopping.
no code implementations • Findings (ACL) 2022 • Hongyuan Lu, Wai Lam, Hong Cheng, Helen Meng
We propose a novel framework that automatically generates a control token with the generator to bias the succeeding response towards informativeness for answerable contexts and fallback for unanswerable contexts in an end-to-end manner.
1 code implementation • EMNLP 2021 • Wenxuan Zhang, Ruidan He, Haiyun Peng, Lidong Bing, Wai Lam
Many efforts have been made in solving the Aspect-based sentiment analysis (ABSA) task.
Aspect-Based Sentiment Analysis (ABSA)
Cross-Lingual Transfer
1 code implementation • Findings (EMNLP) 2021 • Wenxuan Zhang, Yang Deng, Xin Li, Lidong Bing, Wai Lam
This motivates us to investigate the task of ABSA on QA forums (ABSA-QA), aiming to jointly detect the discussed aspects and their sentiment polarities for a given QA pair.
1 code implementation • 16 Nov 2023 • Sen yang, Xin Li, Leyang Cui, Lidong Bing, Wai Lam
Though prompting LLMs with various reasoning structures produces reasoning proofs along with answers, these proofs are not ensured to be causal and reliable due to the inherent defects of LLMs.
no code implementations • 15 Nov 2023 • Chang Gao, Haiyun Jiang, Deng Cai, Shuming Shi, Wai Lam
Most existing chain-of-thought (CoT) prompting methods suffer from the issues of generalizability and consistency, as they often rely on instance-specific solutions that may not be applicable to other cases and lack task-level consistency in their reasoning steps.
no code implementations • 1 Nov 2023 • Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua
Proactive dialogues serve as a practical yet challenging dialogue problem in the era of large language models (LLMs), where the dialogue policy planning is the key to improving the proactivity of LLMs.
1 code implementation • 23 Oct 2023 • Sen yang, Xin Li, Lidong Bing, Wai Lam
However, the knowledge-time association is usually insufficient for the downstream tasks that require reasoning over temporal dependencies between knowledge.
1 code implementation • 19 Oct 2023 • Shuaiyi Li, Yang Deng, Wai Lam
Spatial reasoning in text plays a crucial role in various real-world applications.
1 code implementation • 4 Oct 2023 • Chang Gao, Wenxuan Zhang, Guizhen Chen, Wai Lam
Instruction tuning has emerged as a crucial process for harnessing the capabilities of large language models (LLMs) by providing explicit task instructions, leading to improved performance in various tasks.
no code implementations • 28 Sep 2023 • Yifei Yuan, Wenxuan Zhang, Yang Deng, Wai Lam
Existing work on fashion knowledge extraction in social media is classification-based and requires to manually determine a set of fashion knowledge categories in advance.
no code implementations • 9 Sep 2023 • Hongyuan Lu, Wai Lam
This is well motivated as augmenting data via paraphrasing effectively improves neural language models.
no code implementations • 3 Jun 2023 • Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, Ruifeng Xu
This survey is expected to facilitate researchers' collaborative efforts to tackle the challenges of real-life RE systems.
1 code implementation • 25 May 2023 • Yuejiao Fei, Leyang Cui, Sen yang, Wai Lam, Zhenzhong Lan, Shuming Shi
Grammatical error correction systems improve written communication by detecting and correcting language mistakes.
1 code implementation • 23 May 2023 • Weiwen Xu, Xin Li, Wai Lam, Lidong Bing
mPMR aims to guide multilingual pre-trained language models (mPLMs) to perform natural language understanding (NLU) including both sequence classification and span extraction in multiple languages.
no code implementations • 22 May 2023 • Haoran Yang, Deng Cai, Huayang Li, Wei Bi, Wai Lam, Shuming Shi
We introduce a frustratingly simple, super efficient and surprisingly effective decoding method, which we call Frustratingly Simple Decoding (FSD), for neural text generation.
1 code implementation • 17 May 2023 • Hanxu Hu, Hongyuan Lu, Huajian Zhang, Yun-Ze Song, Wai Lam, Yue Zhang
To this end, we propose a novel method called CoS (Chain-of-Symbol Prompting) that represents the complex environments with condensed symbolic spatial representations during the chained intermediate thinking steps.
1 code implementation • 17 May 2023 • Yang Deng, Wenxuan Zhang, Yifei Yuan, Wai Lam
Unlike empathetic dialogues, the system in emotional support conversations (ESC) is expected to not only convey empathy for comforting the help-seeker, but also proactively assist in exploring and addressing their problems during the conversation.
1 code implementation • 16 May 2023 • Chang Gao, Wenxuan Zhang, Wai Lam, Lidong Bing
Information extraction (IE) systems aim to automatically extract structured information, such as named entities, relations between entities, and events, from unstructured texts.
1 code implementation • 16 May 2023 • Chaojun Wang, Yang Liu, Wai Lam
Furthermore, we introduce a full-permutation multi-task learning to alleviate the spurious causal relations from intermediate sequences to the target, which results from exposure bias.
no code implementations • 11 May 2023 • Hongyuan Lu, Haoyang Huang, Dongdong Zhang, Haoran Yang, Wai Lam, Furu Wei
Large language models (LLMs) have shown surprisingly good performance in multilingual neural machine translation (MNMT) even when trained without parallel data.
no code implementations • 4 May 2023 • Yang Deng, Wenqiang Lei, Wai Lam, Tat-Seng Chua
Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side.
no code implementations • 8 Apr 2023 • Zihao Fu, Wai Lam, Qian Yu, Anthony Man-Cho So, Shengding Hu, Zhiyuan Liu, Nigel Collier
Grounded on our analysis, we propose a novel partial attention language model to solve the attention degeneration problem.
no code implementations • 16 Feb 2023 • Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam
Product question answering (PQA), aiming to automatically provide instant responses to customer's questions in E-Commerce platforms, has drawn increasing attention in recent years.
no code implementations • 15 Dec 2022 • Hongyuan Lu, Haoyang Huang, Shuming Ma, Dongdong Zhang, Wai Lam, Furu Wei
Despite the success of multilingual sequence-to-sequence pre-training, most existing approaches rely on document-level monolingual corpora in many different languages, sentence-level bilingual corpora,\footnote{In this paper, we use `bilingual corpora' to denote parallel corpora with `bilingual translation pairs' in many different language pairs, each consisting of two sentences/documents with the same meaning written in different languages.
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+3
1 code implementation • 9 Dec 2022 • Weiwen Xu, Xin Li, Wenxuan Zhang, Meng Zhou, Wai Lam, Luo Si, Lidong Bing
We present Pre-trained Machine Reader (PMR), a novel method for retrofitting pre-trained masked language models (MLMs) to pre-trained machine reading comprehension (MRC) models without acquiring labeled data.
1 code implementation • 28 Nov 2022 • Zihao Fu, Haoran Yang, Anthony Man-Cho So, Wai Lam, Lidong Bing, Nigel Collier
How to choose the tunable parameters?
1 code implementation • 23 Oct 2022 • Yifei Yuan, Chen Shi, Runze Wang, Liyi Chen, Feijun Jiang, Yuan You, Wai Lam
In this paper, we propose the task of multimodal conversational query rewrite (McQR), which performs query rewrite under the multimodal visual conversation setting.
1 code implementation • 23 Oct 2022 • Chang Gao, Bowen Li, Wenxuan Zhang, Wai Lam, Binhua Li, Fei Huang, Luo Si, Yongbin Li
Text-to-SQL parsing tackles the problem of mapping natural language questions to executable SQL queries.
1 code implementation • 18 Oct 2022 • Deng Cai, Xin Li, Jackie Chun-Sing Ho, Lidong Bing, Wai Lam
Unlike most prior work that only evaluates the ability to measure semantic similarity, we present a thorough evaluation of existing multilingual sentence embeddings and our improved versions, which include a collection of five transfer tasks in different downstream applications.
1 code implementation • 17 Oct 2022 • Weiwen Xu, Yang Deng, Wenqiang Lei, Wenlong Zhao, Tat-Seng Chua, Wai Lam
We study automatic Contract Clause Extraction (CCE) by modeling implicit relations in legal contracts.
1 code implementation • 17 Oct 2022 • Yang Deng, Wenqiang Lei, Wenxuan Zhang, Wai Lam, Tat-Seng Chua
To facilitate conversational question answering (CQA) over hybrid contexts in finance, we present a new dataset, named PACIFIC.
1 code implementation • 17 Oct 2022 • Weiwen Xu, Xin Li, Yang Deng, Wai Lam, Lidong Bing
Specifically, a novel Peer Data Augmentation (PeerDA) approach is proposed which employs span pairs with the PR relation as the augmentation data for training.
no code implementations • 28 Sep 2022 • Hongyuan Lu, Haoyang Huang, Shuming Ma, Dongdong Zhang, Furu Wei, Wai Lam
Despite the fact that multilingual agreement (MA) has shown its importance for multilingual neural machine translation (MNMT), current methodologies in the field have two shortages: (i) require parallel data between multiple language pairs, which is not always realistic and (ii) optimize the agreement in an ambiguous direction, which hampers the translation performance.
no code implementations • 26 Sep 2022 • Zihao Fu, Yijiang River Dong, Lidong Bing, Wai Lam
As the development of the encoder-decoder architecture, researchers are able to study the text generation tasks with broader types of data.
1 code implementation • 17 Aug 2022 • Hongyuan Lu, Wai Lam
This paper presents \textbf{PCC}: \textbf{P}araphrasing with Bottom-k Sampling and \textbf{C}yclic Learning for \textbf{C}urriculum Data Augmentation, a novel CDA framework via paraphrasing, which exploits the textual paraphrase similarity as the curriculum difficulty measure.
1 code implementation • ACL 2022 • Chang Gao, Wenxuan Zhang, Wai Lam
The goal-oriented document-grounded dialogue aims at responding to the user query based on the dialogue context and supporting document.
1 code implementation • 14 Apr 2022 • Yang Deng, Wenxuan Zhang, Weiwen Xu, Wenqiang Lei, Tat-Seng Chua, Wai Lam
In this work, we propose a novel Unified MultI-goal conversational recommeNDer system, namely UniMIND.
no code implementations • 10 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.
1 code implementation • 2 Mar 2022 • Wenxuan Zhang, Xin Li, Yang Deng, Lidong Bing, Wai Lam
More specifically, we provide a new taxonomy for ABSA which organizes existing studies from the axes of concerned sentiment elements, with an emphasis on recent advances of compound ABSA tasks.
no code implementations • 28 Feb 2022 • Weiwen Xu, Bowei Zou, Wai Lam, Ai Ti Aw
Recent techniques in Question Answering (QA) have gained remarkable performance improvement with some QA models even surpassed human performance.
1 code implementation • 7 Feb 2022 • Yang Deng, Wenxuan Zhang, Wai Lam, Hong Cheng, Helen Meng
In this paper, we propose a novel framework, namely USDA, to incorporate the sequential dynamics of dialogue acts for predicting user satisfaction, by jointly learning User Satisfaction Estimation and Dialogue Act Recognition tasks.
1 code implementation • 27 Dec 2021 • Yang Deng, Yaliang Li, Wenxuan Zhang, Bolin Ding, Wai Lam
Recently, Product Question Answering (PQA) on E-Commerce platforms has attracted increasing attention as it can act as an intelligent online shopping assistant and improve the customer shopping experience.
no code implementations • 27 Nov 2021 • Hongyuan Lu, Wai Lam, Hong Cheng, Helen M. Meng
We incorporate reinforcement learning with a dedicatedly designed critic network for reward judgement.
no code implementations • 15 Nov 2021 • Yifei Yuan, Wai Lam
One characteristic of our model is that it extracts fashion attributes and integrates them with the image vision information for effective representation.
1 code implementation • EMNLP 2021 • Wenxuan Zhang, Yang Deng, Xin Li, Yifei Yuan, Lidong Bing, Wai Lam
Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years, which typically involves four fundamental sentiment elements, including the aspect category, aspect term, opinion term, and sentiment polarity.
Ranked #3 on
Aspect-Based Sentiment Analysis (ABSA)
on TASD
Aspect-Based Sentiment Analysis (ABSA)
Paraphrase Generation
1 code implementation • Findings (EMNLP) 2021 • Deng Cai, Xin Li, Jackie Chun-Sing Ho, Lidong Bing, Wai Lam
We study multilingual AMR parsing from the perspective of knowledge distillation, where the aim is to learn and improve a multilingual AMR parser by using an existing English parser as its teacher.
1 code implementation • Findings (EMNLP) 2021 • Weiwen Xu, Yang Deng, Huihui Zhang, Deng Cai, Wai Lam
We propose a novel Chain Guided Retriever-reader ({\tt CGR}) framework to model the reasoning chain for multi-hop Science Question Answering.
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.
1 code implementation • RANLP 2021 • Haoran Yang, Wai Lam
In this paper, we propose a new framework that considers sentence structure via a sentence structure graph and word relationship via a word similarity graph.
1 code implementation • ACL 2021 • Wenxuan Zhang, Xin Li, Yang Deng, Lidong Bing, Wai Lam
Aspect-based sentiment analysis (ABSA) has received increasing attention recently.
Ranked #4 on
Aspect Sentiment Triplet Extraction
on ASTE-Data-V2
Aspect-Based Sentiment Analysis (ABSA)
Aspect Sentiment Triplet Extraction
+1
no code implementations • WNUT (ACL) 2021 • Yang Deng, Wenxuan Zhang, Wai Lam
In this work, we propose a novel and easy-to-apply data augmentation strategy, namely Bilateral Generation (BiG), with a contrastive training objective for improving the performance of ranking question answer pairs with existing labeled data.
1 code implementation • 8 Jun 2021 • Yifei Yuan, Wai Lam
We study the task of conversational fashion image retrieval via multiturn natural language feedback.
1 code implementation • Findings (ACL) 2021 • Weiwen Xu, Huihui Zhang, Deng Cai, Wai Lam
Our framework contains three new ideas: (a) {\tt AMR-SG}, an AMR-based Semantic Graph, constructed by candidate fact AMRs to uncover any hop relations among question, answer and multiple facts.
1 code implementation • ACL 2021 • Deng Cai, Yan Wang, Huayang Li, Wai Lam, Lemao Liu
Second, the memory retriever and NMT model can be jointly optimized for the ultimate translation goal.
no code implementations • 20 May 2021 • Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, Wai Lam
However, existing methods mainly target at solving one or two of these three decision-making problems in CRS with separated conversation and recommendation components, which restrict the scalability and generality of CRS and fall short of preserving a stable training procedure.
no code implementations • 12 Apr 2021 • Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen
Answer selection, which is involved in many natural language processing applications such as dialog systems and question answering (QA), is an important yet challenging task in practice, since conventional methods typically suffer from the issues of ignoring diverse real-world background knowledge.
1 code implementation • 15 Jan 2021 • Mudit Chaudhary, Borislav Dzodzo, Sida Huang, Chun Hei Lo, Mingzhi Lyu, Lun Yiu Nie, Jinbo Xing, Tianhua Zhang, Xiaoying Zhang, Jingyan Zhou, Hong Cheng, Wai Lam, Helen Meng
Dialog systems enriched with external knowledge can handle user queries that are outside the scope of the supporting databases/APIs.
1 code implementation • 29 Dec 2020 • Zihao Fu, Wai Lam, Anthony Man-Cho So, Bei Shi
The experimental results show that our theoretical framework is applicable in general generation models and our proposed rebalanced encoding approach alleviates the repetition problem significantly.
no code implementations • 21 Dec 2020 • Deng Cai, Yizhe Zhang, Yichen Huang, Wai Lam, Bill Dolan
We propose the task of narrative incoherence detection as a new arena for inter-sentential semantic understanding: Given a multi-sentence narrative, decide whether there exist any semantic discrepancies in the narrative flow.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Yifei Yuan, Jingbo Zhou, Wai Lam
Point-of-Interest (POI) oriented question answering (QA) aims to return a list of POIs given a question issued by a user.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Zihao Fu, Bei Shi, Lidong Bing, Wai Lam
In our architecture, we reconstruct KB triples or texts via a closed-loop framework via linking a generator and an extractor.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Wenxuan Zhang, Qian Yu, Wai Lam
Providing instant response for product-related questions in E-commerce question answering platforms can greatly improve users{'} online shopping experience.
no code implementations • COLING 2020 • Zihao Fu, Lidong Bing, Wai Lam, Shoaib Jameel
Recently, many KB-to-text generation tasks have been proposed to bridge the gap between knowledge bases and natural language by directly converting a group of knowledge base triples into human-readable sentences.
no code implementations • COLING 2020 • Yang Deng, Wenxuan Zhang, Wai Lam
Multi-turn response selection has been extensively studied and applied to many real-world applications in recent years.
no code implementations • 23 Oct 2020 • Xin Li, Lidong Bing, Wenxuan Zhang, Zheng Li, Wai Lam
Cross-lingual adaptation with multilingual pre-trained language models (mPTLMs) mainly consists of two lines of works: zero-shot approach and translation-based approach, which have been studied extensively on the sequence-level tasks.
1 code implementation • EMNLP 2020 • Yang Deng, Wenxuan Zhang, Wai Lam
Question-driven summarization has been recently studied as an effective approach to summarizing the source document to produce concise but informative answers for non-factoid questions.
1 code implementation • EMNLP 2020 • Zihao Fu, Bei Shi, Wai Lam, Lidong Bing, Zhiyuan Liu
This kind of data is much easier to obtain since it can be produced automatically.
no code implementations • 19 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.
1 code implementation • 27 Aug 2020 • Yang Deng, Wenxuan Zhang, Wai Lam
There are two main challenges when exploiting the opinion information from the reviews to facilitate the opinion-aware answer generation: (i) jointly modeling opinionated and interrelated information between the question and reviews to capture important information for answer generation, (ii) aggregating diverse opinion information to uncover the common opinion towards the given question.
1 code implementation • 14 Jul 2020 • Lun Yiu Nie, Cuiyun Gao, Zhicong Zhong, Wai Lam, Yang Liu, Zenglin Xu
In this paper, we propose a novel Contextualized code representation learning strategy for commit message Generation (CoreGen).
no code implementations • 28 Jun 2020 • Wenxuan Zhang, Yang Deng, Wai Lam
In this paper, we investigate the answer ranking problem for product-related questions, with the relevant reviews treated as auxiliary information that can be exploited for facilitating the ranking.
no code implementations • 27 Apr 2020 • Iyiola E. Olatunji, Xin Li, Wai Lam
In this paper, we propose a neural deep learning model that predicts the helpfulness score of a review.
3 code implementations • ACL 2020 • Deng Cai, Wai Lam
We propose a new end-to-end model that treats AMR parsing as a series of dual decisions on the input sequence and the incrementally constructed graph.
Ranked #3 on
AMR Parsing
on LDC2014T12
no code implementations • 7 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.
1 code implementation • 13 Mar 2020 • Wenxuan Zhang, Wai Lam, Yang Deng, Jing Ma
In this paper, we propose the Review-guided Answer Helpfulness Prediction (RAHP) model that not only considers the interactions between QA pairs but also investigates the opinion coherence between the answer and crowds' opinions reflected in the reviews, which is another important factor to identify helpful answers.
no code implementations • 26 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.
1 code implementation • 22 Nov 2019 • Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
Community question answering (CQA) gains increasing popularity in both academy and industry recently.
1 code implementation • 18 Nov 2019 • Deng Cai, Wai Lam
The dominant graph-to-sequence transduction models employ graph neural networks for graph representation learning, where the structural information is reflected by the receptive field of neurons.
no code implementations • ACL 2020 • Qian Yu, Lidong Bing, Qiong Zhang, Wai Lam, Luo Si
We propose an iterative learning framework for handling this challenge via adaptive transfer and augmentation of the training instances with the help of the available user-posed question-answer data.
1 code implementation • WS 2019 • Xin Li, Lidong Bing, Wenxuan Zhang, Wai Lam
In this paper, we investigate the modeling power of contextualized embeddings from pre-trained language models, e. g. BERT, on the E2E-ABSA task.
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.
1 code implementation • IJCNLP 2019 • Deng Cai, Wai Lam
The output graph spans the nodes by the distance to the root, following the intuition of first grasping the main ideas then digging into more details.
Ranked #25 on
AMR Parsing
on LDC2017T10
1 code implementation • NAACL 2019 • Zihao Fu, Yankai Lin, Zhiyuan Liu, Wai Lam
We also propose a novel auto-encoder based facet component to estimate some facets of the fact.
no code implementations • 6 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.
1 code implementation • 13 Nov 2018 • Xin Li, Lidong Bing, Piji Li, Wai Lam
Target-based sentiment analysis involves opinion target extraction and target sentiment classification.
Aspect-Based Sentiment Analysis (ABSA)
Sentiment Classification
1 code implementation • EMNLP 2018 • Yi Liao, Lidong Bing, Piji Li, Shuming Shi, Wai Lam, Tong Zhang
For example, an input sequence could be a word sequence, such as review sentence and advertisement text.
1 code implementation • NAACL 2019 • Deng Cai, Yan Wang, Victoria Bi, Zhaopeng Tu, Xiaojiang Liu, Wai Lam, Shuming Shi
Such models rely on insufficient information for generating a specific response since a certain query could be answered in multiple ways.
no code implementations • COLING 2018 • Qian Yu, Wai Lam, ZiHao Wang
Providing instant responses for product questions in E-commerce sites can significantly improve satisfaction of potential consumers.
no code implementations • ACL 2018 • Bei Shi, Zihao Fu, Lidong Bing, Wai Lam
Given reviews from different domains, some existing methods for word embeddings exploit sentiment information, but they cannot produce domain-sensitive embeddings.
2 code implementations • ACL 2018 • Xin Li, Lidong Bing, Wai Lam, Bei Shi
Between the two layers, we propose a component to generate target-specific representations of words in the sentence, meanwhile incorporate a mechanism for preserving the original contextual information from the RNN layer.
Ranked #19 on
Aspect-Based Sentiment Analysis (ABSA)
on SemEval 2014 Task 4 Sub Task 2
(Laptop (Acc) metric)
1 code implementation • 2 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.
1 code implementation • EMNLP 2018 • Yi Liao, Lidong Bing, Piji Li, Shuming Shi, Wai Lam, Tong Zhang
For example, an input sequence could be a word sequence, such as review sentence and advertisement text.
no code implementations • 28 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.
no code implementations • EMNLP 2017 • Piji Li, Wai Lam, Lidong Bing, Weiwei Guo, Hang Li
The attention weights are learned automatically by an unsupervised data reconstruction framework which can capture the sentence salience.
no code implementations • EMNLP 2017 • Xin Li, Wai Lam
We propose a novel LSTM-based deep multi-task learning framework for aspect term extraction from user review sentences.
Aspect-Based Sentiment Analysis (ABSA)
Multi-Task Learning
+1
no code implementations • WS 2017 • Piji Li, Lidong Bing, Wai Lam
We investigate the problem of reader-aware multi-document summarization (RA-MDS) and introduce a new dataset for this problem.
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).
Ranked #5 on
Text Summarization
on DUC 2004 Task 1
no code implementations • 1 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.
no code implementations • 21 Jun 2017 • Bei Shi, Wai Lam, Shoaib Jameel, Steven Schockaert, Kwun Ping Lai
Word embedding models such as Skip-gram learn a vector-space representation for each word, based on the local word collocation patterns that are observed in a text corpus.
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.
no code implementations • 28 Apr 2015 • Piji Li, Lidong Bing, Wai Lam, Hang Li, Yi Liao
We propose a new MDS paradigm called reader-aware multi-document summarization (RA-MDS).