Papers with Code 아카이브
Stance Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 22
- 보존된 평가 기록
- 28
Stance detection is the extraction of a subject's reaction to a claim made by a primary actor. It is a core part of a set of approaches to fake news assessment.
Example:
- Source: "Apples are the most delicious fruit in existence"
- Reply: "Obviously not, because that is a reuben from Katz's"
- Stance: deny
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ankitp544/stance_detection
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/cambridge-wtwt/emnlp2020-stander-news
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
https://github.com/chiahuiliu/FNC_Python3
A Retrospective Analysis of the Fake News Challenge Stance Detection Task
https://github.com/chimera-detector/Extension
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/chimera-detector/Server
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/chimera-detector/experienceExtension
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/chncwang/InsNet
Unseen Target Stance Detection with Adversarial Domain Generalization
https://github.com/copenlu/TESTED
https://github.com/gabrielsaruhashi/anti-fake
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/harshita97/hoaxbait
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/imran3180/pytorch-nli
https://github.com/lastmile-ai/aiconfig
Chain-of-Thought Embeddings for Stance Detection on Social Media
https://github.com/lyh6560new/p3sum
https://github.com/nicolay-r/RuSentRel-Leaderboard
How would Stance Detection Techniques Evolve after the Launch of ChatGPT?
https://github.com/pmallari/AmazonSentimentAnalysis
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/prithivirajdamodaran/flashrank
https://github.com/radiukpavlo/transition-matrix-dl
https://github.com/ragerri/multilingual-stance-lrec2020
Multilingual Stance Detection: The Catalonia Independence Corpus
https://github.com/seongjinpark-88/RumorEval2019
Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM
https://github.com/sugoiii/detecting-incongruity-dataset-gen
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
https://github.com/uclnlp/fakenewschallenge
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
https://github.com/vineet2104/StanceDetection-CS626
On the Benefit of Combining Neural, Statistical and External Features for Fake News Identification
https://github.com/yinghao1019/imdb_prac
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.