Community Question Answering
42 papers with code • 2 benchmarks • 6 datasets
Community question answering is the task of answering questions on a Q&A forum or board, such as Stack Overflow or Quora.
Benchmarks
These leaderboards are used to track progress in Community Question Answering
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Quora Question Pairs
AmazonQA
ANTIQUE
Most implemented papers
Utilizing Bidirectional Encoder Representations from Transformers for Answer Selection
tahmedge/BERT-for-Answer-Selection
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We find that fine-tuning the BERT model for the answer selection task is very effective and observe a maximum improvement of 13. 1% in the QA datasets and 18. 7% in the CQA datasets compared to the previous state-of-the-art.
Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matching
However, these models designed for short texts cannot well address the long-form text matching problem, because there are many contexts in long-form texts can not be directly aligned with each other, and it is difficult for existing models to capture the key matching signals from such noisy data.
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining
Yale-LILY/ConvoSumm
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ACL 2021
While online conversations can cover a vast amount of information in many different formats, abstractive text summarization has primarily focused on modeling solely news articles.
Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework
abhi1nandy2/emnlp-2021-findings
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Findings (EMNLP) 2021
Answering questions asked from instructional corpora such as E-manuals, recipe books, etc., has been far less studied than open-domain factoid context-based question answering.
AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization
alex-fabbri/answersumm
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NAACL 2022
One goal of answer summarization is to produce a summary that reflects the range of answer perspectives.
HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling
Most of the CQA methods only incorporate articles or Wikipedia to extract knowledge and answer the user's question.
Expert Finding in Legal Community Question Answering
In the legal domain, there is a large knowledge gap between the experts and the searchers, and the content on the legal QA websites consist of a combination formal and informal communication.
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents
rowitzou/dc-match
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Findings (ACL) 2022
Text semantic matching is a fundamental task that has been widely used in various scenarios, such as community question answering, information retrieval, and recommendation.
CHQ-Summ: A Dataset for Consumer Healthcare Question Summarization
The quest for seeking health information has swamped the web with consumers' health-related questions.
SE-PQA: Personalized Community Question Answering
pkasela/se-pqa
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Personalization in Information Retrieval is a topic studied for a long time.
