https://github.com/DaBr01/AGB-DE
공식 코드AGB-DE: A Corpus for the Automated Legal Assessment of Clauses in German Consumer Contracts
Papers with Code 아카이브
Binary text classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dongping-chen/mixset
공식 코드LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?
https://github.com/hsuvas/hoaxpedia_dataset
공식 코드https://github.com/muzaluisa/soft-skill-matching
공식 코드https://github.com/sruthisudheer/comment-classification-of-c-code
공식 코드Identification of the Relevance of Comments in Codes Using Bag of Words and Transformer Based Models
https://github.com/tizfa/tweepfake_deepfake_text_detection
공식 코드https://github.com/vivek3141/ghostbuster
공식 코드Ghostbuster: Detecting Text Ghostwritten by Large Language Models
https://github.com/vivek3141/ghostbuster-data
공식 코드Ghostbuster: Detecting Text Ghostwritten by Large Language Models
https://github.com/yafuly/deepfaketextdetect
공식 코드https://github.com/yafuly/mage
공식 코드https://github.com/MindSpore-paper-code-3/code9/tree/main/transformer_xl
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
https://github.com/amritabh/chatgpt-as-detector
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
https://github.com/amritabh/conda-gen-text-detection
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
https://github.com/dongping-chen/mllm-as-a-judge
LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?
https://github.com/muzaluisa/Learning_Representations_for_Soft_Skill_Matching
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.