https://github.com/yoonnajang/rem
공식 코드Post-hoc Utterance Refining Method by Entity Mining for Faithful Knowledge Grounded Conversations
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/yrf1/russiaukraine_weibo_dataset
공식 코드https://github.com/yuangan/silencer
공식 코드https://github.com/yuanyuanlei-nlp/conspiracy_theories_emnlp_2023
공식 코드Identifying Conspiracy Theories News based on Event Relation Graph
https://github.com/yueeeeeeee/canmd
공식 코드Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19
https://github.com/yueeeeeeee/metaadapt
공식 코드MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Meta Learning
https://github.com/yunshiuan/llm-agent-opinion-dynamics
공식 코드Simulating Opinion Dynamics with Networks of LLM-based Agents
https://github.com/yvonnemamama/ggd
공식 코드https://github.com/yxf203/poisonarena
공식 코드PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation
https://github.com/zainali93/UrduHMFND2024
공식 코드https://github.com/zbox1005/cot-uq
공식 코드CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought
https://github.com/zexihuang/pole
공식 코드https://github.com/zfr00/fact-r1
공식 코드Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning
https://github.com/zhaochen0110/conflictbank
공식 코드ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLM
https://github.com/zhenglisec/unganable
공식 코드https://github.com/zhongping-zhang/mgt_localization
공식 코드https://github.com/zhpinkman/cbr
공식 코드Case-Based Reasoning with Language Models for Classification of Logical Fallacies
https://github.com/zhrli324/argus
공식 코드Goal-Aware Identification and Rectification of Misinformation in Multi-Agent Systems
https://github.com/zz1358m/reasoning-cv
공식 코드Reasoning-CV: Fine-tuning Powerful Reasoning LLMs for Knowledge-Assisted Claim Verification
https://github.com/zzoliman/covid-vaccine-misinfo-mic
공식 코드https://gitlab.com/notredame-provenance/u-phylogeny
공식 코드U-Phylogeny: Undirected Provenance Graph Construction in the Wild
https://zenodo.org/record/6842883
공식 코드https://github.com/BinWang28/BERT_Sentence_Embedding
Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
https://github.com/BinWang28/SBERT-WK-Sentence-Embedding
Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
https://github.com/BunsenFeng/modular_pluralism
https://github.com/CASOS-IDeaS-CMU/Detection-and-Discovery-of-Misinformation-Sources
https://github.com/HLTCHKUST/UnifiedM2
https://github.com/Kanaderu/nlp_credibility
DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning
https://github.com/Komal7209/BackUp-Twitter-Sentiment-Analysis-
COVID-19 on Social Media: Analyzing Misinformation in Twitter Conversations
https://github.com/Komal7209/Covid19TwitterSentiment-Analysis
COVID-19 on Social Media: Analyzing Misinformation in Twitter Conversations
https://github.com/LiamMaclean216/Pytorch-Transfomer
Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
https://github.com/MindCode-4/code-7/tree/main/misinfo-reaction-frames
Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines
https://github.com/MuMiN-dataset/mumin-baseline
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset
https://github.com/MuMiN-dataset/mumin-trawl
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset
https://github.com/R2th/Covid-19-Fake-News-Detection-System
Transformer based Automatic COVID-19 Fake News Detection System
https://github.com/ShyamSubramanian/HESM
Combining Fact Extraction and Verification with Neural Semantic Matching Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.