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Dialogue Evaluation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/SarikGhazarian/PredictiveEngagement
공식 코드Predictive Engagement: An Efficient Metric For Automatic Evaluation of Open-Domain Dialogue Systems
https://github.com/alexa/conture
공식 코드What is wrong with you?: Leveraging User Sentiment for Automatic Dialog Evaluation
https://github.com/asmadotgh/neural_chat_web
공식 코드Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
https://github.com/bernard-yang/simamr
공식 코드https://github.com/ddehun/density
공식 코드DEnsity: Open-domain Dialogue Evaluation Metric using Density Estimation
https://github.com/ddehun/paireval
공식 코드PairEval: Open-domain Dialogue Evaluation with Pairwise Comparison
https://github.com/dialogue-evaluation/RuOpinionNE-2024
공식 코드RuOpinionNE-2024: Extraction of Opinion Tuples from Russian News Texts
https://github.com/dialogue-evaluation/ruatd
공식 코드Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian
https://github.com/dialogue-evaluation/runne
공식 코드https://github.com/e0397123/DynaEval
공식 코드https://github.com/e0397123/FineD-Eval
공식 코드FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation
https://github.com/e0397123/comp-analysis
공식 코드https://github.com/e0397123/find-eval
공식 코드FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation
https://github.com/e0397123/mdd-eval
공식 코드MDD-Eval: Self-Training on Augmented Data for Multi-Domain Dialogue Evaluation
https://github.com/e0397123/xdial-eval
공식 코드xDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark
https://github.com/emora-chat/chatevaluationplatform
공식 코드Don't Forget Your ABC's: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems
https://github.com/emorynlp/chatevaluationplatform
공식 코드Don't Forget Your ABC's: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems
https://github.com/exe1023/DialEvalMetrics
공식 코드https://github.com/facebookresearch/online_dialog_eval
공식 코드Learning an Unreferenced Metric for Online Dialogue Evaluation
https://github.com/fulstock/Methods-for-Recognizing-Nested-Terms
공식 코드https://github.com/golsun/AdversarialTuringTest
공식 코드An Adversarially-Learned Turing Test for Dialog Generation Models
https://github.com/harsh19/Diverse-Reference-Augmentation
공식 코드Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
https://github.com/hegehongcha/slide-acl2024
공식 코드SLIDE: A Framework Integrating Small and Large Language Models for Open-Domain Dialogues Evaluation
https://github.com/ictnlp/DialoFlow
공식 코드Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances
https://github.com/iitmnlp/Dialogue-Evaluation-with-BERT
공식 코드Improving Dialog Evaluation with a Multi-reference Adversarial Dataset and Large Scale Pretraining
https://github.com/johndmendonca/Ecoh
공식 코드ECoh: Turn-level Coherence Evaluation for Multilingual Dialogues
https://github.com/johndmendonca/dialevalml
공식 코드https://github.com/johndmendonca/medal
공식 코드https://github.com/johndmendonca/soda_eval
공식 코드Soda-Eval: Open-Domain Dialogue Evaluation in the age of LLMs
https://github.com/jvasselli/dialogue-metric-robustness
공식 코드Measuring the Robustness of Reference-Free Dialogue Evaluation Systems
https://github.com/kwai/dialogbench
공식 코드https://github.com/lfdharo/DSTC10_Track5_Toxicity
공식 코드Automatic Evaluation and Moderation of Open-domain Dialogue Systems
https://github.com/li3cmz/GRADE
공식 코드GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems
https://github.com/mike-n-7/ADEM
공식 코드Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses
https://github.com/natashamjaques/neural_chat
공식 코드Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.