krystalan / chatgpt_as_nlg_evaluatorLinks
Technical Report: Is ChatGPT a Good NLG Evaluator? A Preliminary Study
β43Updated 2 years ago
Alternatives and similar repositories for chatgpt_as_nlg_evaluator
Users that are interested in chatgpt_as_nlg_evaluator are comparing it to the libraries listed below
Sorting:
- π©Ί A collection of ChatGPT evaluation reports on various bechmarks.β50Updated 2 years ago
- First explanation metric (diagnostic report) for text generation evaluationβ62Updated 9 months ago
- We construct and introduce DIALFACT, a testing benchmark dataset crowd-annotated conversational claims, paired with pieces of evidence frβ¦β44Updated 3 years ago
- β27Updated 3 years ago
- Code for the paper Code for the paper InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuningβ100Updated 2 years ago
- [EMNLP 2022] Code and data for "Controllable Dialogue Simulation with In-Context Learning"β35Updated 2 years ago
- Dataset for TACL 2022 paper: "FeTaQA: Free-form Table Question Answering"β85Updated 2 years ago
- An Interpretable Neuro-Symbolic Framework for Task-Oriented Dialogue Generationβ23Updated 3 years ago
- β88Updated 2 years ago
- The project page for "SCITAB: A Challenging Benchmark for Compositional Reasoning and Claim Verification on Scientific Tables"β23Updated 2 years ago
- Code for EMNLP 2021 paper "CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization"β46Updated 3 years ago
- β14Updated 2 years ago
- [ACL 2022] Ditch the Gold Standard: Re-evaluating Conversational Question Answeringβ44Updated 3 years ago
- β82Updated 2 years ago
- β32Updated 2 years ago
- Official code for "Continual Prompt Tuning for Dialog State Tracking" (ACL 2022).β27Updated 2 years ago
- The code of Paper "Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering".β21Updated 3 years ago
- Code base of In-Context Learning for Dialogue State trackingβ45Updated 2 years ago
- β69Updated 3 years ago
- β64Updated 3 years ago
- Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors (ACL 2023)β28Updated last year
- The code implementation of the EMNLP2022 paper: DisCup: Discriminator Cooperative Unlikelihood Prompt-tuning for Controllable Text Geneβ¦β27Updated 2 years ago
- This project maintains a reading list for general text generation tasksβ66Updated 4 years ago
- An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"β131Updated 3 years ago
- Code and resources for papers "Generation-Augmented Retrieval for Open-Domain Question Answering" and "Reader-Guided Passage Reranking foβ¦β74Updated 3 years ago
- WikiWhy is a new benchmark for evaluating LLMs' ability to explain between cause-effect relationships. It is a QA dataset containing 9000β¦β48Updated 2 years ago
- β19Updated 3 years ago
- β36Updated last year
- Resources for our ACL 2023 paper: Distilling Script Knowledge from Large Language Models for Constrained Language Planningβ36Updated 2 years ago
- Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"β59Updated 3 years ago