https://github.com/mbzuai-nlp/x-claim
공식 코드Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media
Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checking
Zero-Shot Learning and Key Points Are All You Need for Automated Fact-Checking
CrowdChecked: Detecting Previously Fact-Checked Claims in Social Media
Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference
AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web
The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Who
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Optimizing Retrieval-augmented Reader Models via Token Elimination
ChartCheck: Explainable Fact-Checking over Real-World Chart Images
DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts
Factuality Enhanced Language Models for Open-Ended Text Generation
Discriminative Predicate Path Mining for Fact Checking in Knowledge Graphs
Explainable Automated Fact-Checking for Public Health Claims
The Rise of Guardians: Fact-checking URL Recommendation to Combat Fake News
Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News
Learning from Fact-checkers: Analysis and Generation of Fact-checking Language
Attributed Multi-Relational Attention Network for Fact-checking URL Recommendation
A Multi-Level Attention Model for Evidence-Based Fact Checking
How We Refute Claims: Automatic Fact-Checking through Flaw Identification and Explanation
How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation
Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needs
Science Checker: Extractive-Boolean Question Answering For Scientific Fact Checking
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.