태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Matching a target text to a source text based on their meaning.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
MedICaT is a dataset of medical images, captions, subfigure-subcaption annotations, and inline textual references. Figures and captions are extracted from open access articles in PubMed Central and corresponding reference text is derived from S2ORC. The dataset consists of: 217,060 figures from 131,410 open access papers 7507 subcaption and subfigure annotations for 2069 compound figures Inline references for ~25K figures in the ROCO dataset Source: https://github.com/allenai/medicat
Fact-checking (FC) articles which contains pairs (multimodal tweet and a FC-article) from snopes.com. Source: Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News
Fact-checking (FC) articles which contains pairs (multimodal tweet and a FC-article) from politifact.com. Source: Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News
DuLeMon is a large-scale Chinese Long-term Memory Conversation dataset, which simulates long-term memory conversations and focuses on the ability to actively construct and utilize the user's and the bot's persona in a long-term interaction. DuLeMon contains about 27.5k human-human conversations, 449k utterances, and 12k persona grounding sentences. This corpus can be used to explore Long-term Memory Conversation, Personalized Dialogue, and Persona Extraction / Matching / Retrieval.
A large-scale curated dataset of over 152 million tweets, growing daily, related to COVID-19 chatter generated from January 1st to April 4th at the time of writing. Source: A large-scale COVID-19 Twitter chatter dataset for open scientific research -- an international collaboration
The Composed Quora dataset consists of questions extracted from Quora that are grouped together if they are asking the same thing. The dataset contains 60,400 groups of questions, each group with at least 3 questions that are asking the same. Source: https://arxiv.org/pdf/1911.02747.pdf
PSM is a financial-domain dataset of the pairwise search matching task. It aims to identify the semantic similarity of a sentence pair in the search scenario.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.