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20192023
most citedSentiment Analysis in the Era of Large Language Models: A Reality Check

56 citations · 268 across the 22 of their papers we have counts for

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Showing cs.CLShow all

17 papers · 1 filter

cs.CL2023★ 32 cited

M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models

Wenxuan Zhang, Sharifah Mahani Aljunied, Chang Gao +2

Despite the existence of various benchmarks for evaluating natural language processing models, we argue that human exams are a more suitable means of evaluating general intelligenc…

cs.CL2023

AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative Approach

Jia Guo, Liying Cheng, Wenxuan Zhang +3

Argument mining involves multiple sub-tasks that automatically identify argumentative elements, such as claim detection, evidence extraction, stance classification, etc. However, e…

cs.CL2023★ 2 cited

Zero-Shot Text Classification via Self-Supervised Tuning

Chaoqun Liu, Wenxuan Zhang, Guizhen Chen +4

Existing solutions to zero-shot text classification either conduct prompting with pre-trained language models, which is sensitive to the choices of templates, or rely on large-scal…

cs.CL2023★ 56 cited

Sentiment Analysis in the Era of Large Language Models: A Reality Check

Wenxuan Zhang, Yue Deng, Bing Liu +2

Sentiment analysis (SA) has been a long-standing research area in natural language processing. It can offer rich insights into human sentiments and opinions and has thus seen consi…

cs.CL2023★ 4 cited

Enhancing Few-shot NER with Prompt Ordering based Data Augmentation

Huiming Wang, Liying Cheng, Wenxuan Zhang +2

Recently, data augmentation (DA) methods have been proven to be effective for pre-trained language models (PLMs) in low-resource settings, including few-shot named entity recogniti…

cs.CL2023

Easy-to-Hard Learning for Information Extraction

Chang Gao, Wenxuan Zhang, Wai Lam +1

Information extraction (IE) systems aim to automatically extract structured information, such as named entities, relations between entities, and events, from unstructured texts. Wh…

cs.CL2023★ 2 cited

Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversations

Yang Deng, Wenxuan Zhang, Yifei Yuan +1

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…

cs.CL2023

Bidirectional Generative Framework for Cross-domain Aspect-based Sentiment Analysis

Yue Deng, Wenxuan Zhang, Sinno Jialin Pan +1

Cross-domain aspect-based sentiment analysis (ABSA) aims to perform various fine-grained sentiment analysis tasks on a target domain by transferring knowledge from a source domain.…

cs.CL2023

Product Question Answering in E-Commerce: A Survey

Yang Deng, Wenxuan Zhang, Qian Yu +1

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.…

cs.CL2022★ 4 cited

From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Model to Pre-trained Machine Reader

Weiwen Xu, Xin Li, Wenxuan Zhang +4

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 wit…

cs.CL2022

Towards Generalizable and Robust Text-to-SQL Parsing

Chang Gao, Bowen Li, Wenxuan Zhang +5

Text-to-SQL parsing tackles the problem of mapping natural language questions to executable SQL queries. In practice, text-to-SQL parsers often encounter various challenging scenar…

cs.CL2022★ 38 cited

A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges

Wenxuan Zhang, Xin Li, Yang Deng +2

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis (ABSA), aiming to analyze and understand people's opinions at the aspect level, has been at…

cs.CL2021★ 1 cited

Aspect Sentiment Quad Prediction as Paraphrase Generation

Wenxuan Zhang, Yang Deng, Xin Li +3

Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years, which typically involves four fundamental sentiment elements, including the aspect category, as…

cs.CL2020★ 4 cited

Multi-hop Inference for Question-driven Summarization

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 quest…

cs.CL2020★ 25 cited

Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond

Xin Li, Lidong Bing, Wenxuan Zhang +2

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…

cs.CL2020★ 1 cited

Review-guided Helpful Answer Identification in E-commerce

Wenxuan Zhang, Wai Lam, Yang Deng +1

Product-specific community question answering platforms can greatly help address the concerns of potential customers. However, the user-provided answers on such platforms often var…

cs.CL2019★ 47 cited

Exploiting BERT for End-to-End Aspect-based Sentiment Analysis

Xin Li, Lidong Bing, Wenxuan Zhang +1

In this paper, we investigate the modeling power of contextualized embeddings from pre-trained language models, e.g. BERT, on the E2E-ABSA task. Specifically, we build a series of…