https://github.com/less-and-less-bugs/rdcm
공식 코드Robust Domain Misinformation Detection via Multi-modal Feature Alignment
Papers with Code 아카이브
Misinformation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/liwd190019/shallow-diffuse
공식 코드https://github.com/ljyflores/fake-news-explainability
공식 코드https://github.com/llm-misinformation/llm-misinformation
공식 코드https://github.com/lluckyyh/xtrust
공식 코드XTRUST: On the Multilingual Trustworthiness of Large Language Models
https://github.com/lorypack/llm-liedetector
공식 코드How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
https://github.com/ltian678/ic-mamba
공식 코드https://github.com/ltian678/metatroll-code
공식 코드MetaTroll: Few-shot Detection of State-Sponsored Trolls with Transformer Adapters
https://github.com/lucamouchel/Logical-Fallacies
공식 코드A Logical Fallacy-Informed Framework for Argument Generation
https://github.com/luck1y/beamattack
공식 코드Robustness of Misinformation Classification Systems to Adversarial Examples Through BeamAttack
https://github.com/luohongyin/unilc
공식 코드https://github.com/luoundergradxjtu/twibot-22
공식 코드https://github.com/lzw108/conspemollm
공식 코드ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model
https://github.com/lzw108/fmd
공식 코드FMDLlama: Financial Misinformation Detection based on Large Language Models
https://github.com/lzw108/raemollm
공식 코드https://github.com/marcobornstein/AI-Regulatory-Auctions
공식 코드https://github.com/marcoguerini/vermouth
공식 코드https://github.com/marcosfp97/llm-binary-health-qa
공식 코드Evaluating Search Engines and Large Language Models for Answering Health Questions
https://github.com/markotesic/counterfactual_explanations_XAI
공식 코드https://github.com/marsgokturk/gpt3-false-political-statement-detection
공식 코드https://github.com/matheus-schmitz/avaxtar
공식 코드https://github.com/mbzuai-nlp/detectllm
공식 코드DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text
https://github.com/meetyou-ai-lab/care-mi
공식 코드CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care
https://github.com/melaniesubbiah/harmfulagendasnews
공식 코드https://github.com/metunlp/mide22
공식 코드MiDe22: An Annotated Multi-Event Tweet Dataset for Misinformation Detection
https://github.com/mever-team/credule-dataset
공식 코드Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checking
https://github.com/mhmdsaiid/birdwatch
공식 코드Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?
https://github.com/michschli/intendedafcuses
공식 코드The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Who
https://github.com/microsoft/hallucinated-references
공식 코드Do Language Models Know When They're Hallucinating References?
https://github.com/mignonjia/ts_watermark
공식 코드https://github.com/minieggz/effiara
공식 코드https://github.com/minieggz/ruc-misinfo
공식 코드https://github.com/mjsumpter/remod
공식 코드https://github.com/mminici/socgfm
공식 코드IOHunter: Graph Foundation Model to Uncover Online Information Operations
https://github.com/mmlab-unitn/truefake-ijcnn25
공식 코드TrueFake: A Real World Case Dataset of Last Generation Fake Images also Shared on Social Networks
https://github.com/morganlee123/2gptempathicdialogues
공식 코드A Linguistic Comparison between Human and ChatGPT-Generated Conversations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.