Papers with Code 아카이브

Fact Checking

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

5

평가표

7

보존된 평가 기록

19

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/chengxuphd/liar2

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/chrisociepa/allamo

PaLM: Scaling Language Modeling with Pathways

https://github.com/ckinateder/pytsetlinmachineparallel

Explainable Tsetlin Machine framework for fake news detection with credibility score assessment

https://github.com/code-implementation1/Code9/tree/main/gat

User Preference-aware Fake News Detection

https://github.com/conceptofmind/PaLM-flax

PaLM: Scaling Language Modeling with Pathways

https://github.com/copenlu/check-worthiness-pu-learning

Claim Check-Worthiness Detection as Positive Unlabelled Learning

https://github.com/cvrl/scalable_provenance

Image Provenance Analysis at Scale

https://github.com/declare-lab/sancl

Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News

https://github.com/distractor-generation/dg_survey

Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning

https://github.com/ekagra-ranjan/fake-news-detection-LIAR-pytorch

"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

https://github.com/eric-mitchell/mend

Editing Factual Knowledge in Language Models

https://github.com/eric-mitchell/serac

Memory-Based Model Editing at Scale

https://github.com/facebookresearch/editeval

KILT: a Benchmark for Knowledge Intensive Language Tasks

https://github.com/foundation-model-stack/fms-fsdp

PaLM: Scaling Language Modeling with Pathways

https://github.com/freedomintelligence/sdak

FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

https://github.com/gabrevaya/LatentDiffEq

Generative ODE Modeling with Known Unknowns

https://github.com/gabrevaya/LatentDiffEq.jl

Generative ODE Modeling with Known Unknowns

https://github.com/gabrielsaruhashi/anti-fake

A simple but tough-to-beat baseline for the Fake News Challenge stance detection task

https://github.com/google/paxml

PaLM: Scaling Language Modeling with Pathways

https://github.com/gordicaleksa/pytorch-GAT

Fake News Detection on Social Media using Geometric Deep Learning

https://github.com/guijinSON/SPOT

When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research

https://github.com/harshita97/hoaxbait

A simple but tough-to-beat baseline for the Fake News Challenge stance detection task

https://github.com/hawkrobe/division_of_labor

The division of labor in communication: Speakers help listeners account for asymmetries in visual perspective

https://github.com/iit-nlp-research/chatgpt-crawler

FaVIQ: FAct Verification from Information-seeking Questions

https://github.com/j6mes/acl2021-factual-error-correction

Evidence-based Factual Error Correction

https://github.com/jiesutd/PyTorchSeqLabel

Design Challenges and Misconceptions in Neural Sequence Labeling

https://github.com/karpathy/llama2.c

Training Compute-Optimal Large Language Models

https://github.com/kiranrawat/Detecting-Fake-News-On-Social-Media

"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

https://github.com/klemens-floege/svn_ensembles

Laplace Redux -- Effortless Bayesian Deep Learning

https://github.com/kmeng01/rome

Editing Factual Knowledge in Language Models

https://github.com/kyriezoe/Fake_News_Detection

Fake News Detection via NLP is Vulnerable to Adversarial Attacks

https://github.com/learn-co-curriculum/dsc-3-28-12-graph-connectivity-community-detection

Community detection in networks: A user guide

https://github.com/learn-co-curriculum/dsc-graph-connectivity-community-detection

Community detection in networks: A user guide

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.