https://github.com/EnablerRx/CASF
공식 코드Better than Random: Reliable NLG Human Evaluation with Constrained Active Sampling
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nlg evaluation
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Evaluate the generated text by NLG (Natural Language Generation) systems, like large language models
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/EnablerRx/GuidelineVulnDetect
공식 코드https://github.com/MirunaClinciu/ExBAN
공식 코드A Study of Automatic Metrics for the Evaluation of Natural Language Explanations
https://github.com/PKU-ONELab/Themis
공식 코드Themis: A Reference-free NLG Evaluation Language Model with Flexibility and Interpretability
https://github.com/adianliusie/comparative-assessment
공식 코드https://github.com/akashkm99/duelnlg
공식 코드Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons
https://github.com/chongyangtao/LLMs-for-NLG-Evaluation
공식 코드Leveraging Large Language Models for NLG Evaluation: Advances and Challenges
https://github.com/google-research-datasets/clse
공식 코드https://github.com/gu-clasp/describe-me-an-auklet
공식 코드Describe me an Aucklet: Generating Grounded Perceptual Category Descriptions
https://github.com/gunny97/DEBATE
공식 코드DEBATE: Devil's Advocate-Based Assessment and Text Evaluation
https://github.com/herrxy/llm-evaluator-reliability
공식 코드https://github.com/iitmnlp/evaleval
공식 코드Perturbation CheckLists for Evaluating NLG Evaluation Metrics
https://github.com/inimah/metric-preference-checklist
공식 코드NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
https://github.com/isle-dev/metriceval
공식 코드https://github.com/ivankartac/OpeNLGauge
공식 코드OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs
https://github.com/jeknov/EMNLP_17_submission
공식 코드https://github.com/kepei1106/decompeval
공식 코드DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question Answering
https://github.com/kite99520/NLGCorrEval
공식 코드Analyzing and Evaluating Correlation Measures in NLG Meta-Evaluation
https://github.com/krystalan/chatgpt_as_nlg_evaluator
공식 코드https://github.com/maszhongming/unieval
공식 코드Towards a Unified Multi-Dimensional Evaluator for Text Generation
https://github.com/matthewcym/adveval
공식 코드https://github.com/moonlight-syntax/luna
공식 코드LUNA: A Framework for Language Understanding and Naturalness Assessment
https://github.com/nl2g/effeval
공식 코드EffEval: A Comprehensive Evaluation of Efficiency for MT Evaluation Metrics
https://github.com/nlpyang/geval
공식 코드G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
https://github.com/pku-onelab/llm-evaluator-reliability
공식 코드https://github.com/rucaibox/div-ref
공식 코드Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying References
https://github.com/rucaibox/para-ref
공식 코드Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying References
https://github.com/salesforce/nnd_evaluation
공식 코드Near-Negative Distinction: Giving a Second Life to Human Evaluation Datasets
https://github.com/sefazeng/llm-ref
공식 코드https://github.com/tanyuqian/ctc-gen-eval
공식 코드https://github.com/tjsiledar/summeval-op
공식 코드One Prompt To Rule Them All: LLMs for Opinion Summary Evaluation
https://github.com/xu1998hz/sescore
공식 코드Not All Errors are Equal: Learning Text Generation Metrics using Stratified Error Synthesis
https://github.com/zanchangtong/csr4mbart
공식 코드https://github.com/hkust-knowcomp/knowledge-constrained-decoding
Towards a Unified Multi-Dimensional Evaluator for Text Generation
https://github.com/huggingface/transformers
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
https://github.com/megagonlabs/llm-longeval
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.