Dialogue Evaluation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pluslabnlp/deam
공식 코드DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations
https://github.com/prakharguptaz/Adv_gen_dialogue
공식 코드Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation
https://github.com/prakharguptaz/Instructdial
공식 코드InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
https://github.com/prakharguptaz/multirefeval
공식 코드Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple References
https://github.com/renll/c-pmi
공식 코드C-PMI: Conditional Pointwise Mutual Information for Turn-level Dialogue Evaluation
https://github.com/royny/self-eval
공식 코드https://github.com/ruckbreasoning/glm-dialog
공식 코드GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
https://github.com/sashank06/INLG_eval
공식 코드Towards Best Experiment Design for Evaluating Dialogue System Output
https://github.com/sfillwo/dialogueeval-annotatorimpact
공식 코드Exploring the Impact of Human Evaluator Group on Chat-Oriented Dialogue Evaluation
https://github.com/shikib/fed
공식 코드https://github.com/shikib/usr
공식 코드USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation
https://github.com/sopilnyak/headline-selection
공식 코드Transformers for Headline Selection for Russian News Clusters
https://github.com/suvodipdey/bok
공식 코드BoK: Introducing Bag-of-Keywords Loss for Interpretable Dialogue Response Generation
https://github.com/tianboji/dialogue-eval
공식 코드Achieving Reliable Human Assessment of Open-Domain Dialogue Systems
https://github.com/vitouphy/usl_dialogue_metric
공식 코드Deconstruct to Reconstruct a Configurable Evaluation Metric for Open-Domain Dialogue Systems
https://github.com/yhlleo/frechet-bert-distance
공식 코드https://github.com/yubol-cmu/awesome-multi-turn-llms
공식 코드Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models
https://github.com/AIJoris/DPAC-DialogueGAN
https://github.com/CatherineWong/dancin_seq2seq
https://github.com/PlusLabNLP/PredictiveEngagement
Predictive Engagement: An Efficient Metric For Automatic Evaluation of Open-Domain Dialogue Systems
https://github.com/YufanPaPa/GAN_SSN
https://github.com/aqzheng/Adversarial-Learning-for-Neural-Dialogue-Generation
https://github.com/baber-sos/Explaining-Dialogue-Evaluation-Metrics-using-Adversarial-Behavioral-Analysis
https://github.com/e0397123/dstc10_metric_track
Automatic Evaluation and Moderation of Open-domain Dialogue Systems
https://github.com/emorynlp/gpt-abceval
Don't Forget Your ABC's: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems
https://github.com/gmftbyGMFTBY/PONE
PONE: A Novel Automatic Evaluation Metric for Open-Domain Generative Dialogue Systems
https://github.com/jsbaan/DPAC-DialogueGAN
https://github.com/liuyuemaicha/Adversarial-Learning-for-Neural-Dialogue-Generation-in-Tensorflow
https://github.com/orhonovich/q-squared
https://github.com/seungguini/multiref_eval
Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple References
https://github.com/smartdataanalytics/proxy_indicators
https://github.com/thomashuang2017/simpson-dialogue-gan-master
https://github.com/thu-coai/OpenMEVA
RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems
https://github.com/zpschang/seqGAN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.