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Found 8 papers, 6 papers with code
NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?
Artificial Intelligence (AI) has witnessed rapid growth, especially in the subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer Vision (CV).
The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics
Specifically, we propose a novel competition setting in which we select a list of allowed LLMs and disallow fine-tuning to ensure a focus on prompting.
NLLG Quarterly arXiv Report 06/23: What are the most influential current AI Papers?
In particular, we compile a list of the 40 most popular papers based on normalized citation counts from the first half of 2023.
Towards Explainable Evaluation Metrics for Machine Translation
In this context, we also discuss the latest state-of-the-art approaches to explainable metrics based on generative models such as ChatGPT and GPT4.
ChatGPT: A Meta-Analysis after 2.5 Months
ChatGPT, a chatbot developed by OpenAI, has gained widespread popularity and media attention since its release in November 2022.
BMX: Boosting Natural Language Generation Metrics with Explainability
We then combine this segment-level score with the original metric to obtain a better metric.
EffEval: A Comprehensive Evaluation of Efficiency for MT Evaluation Metrics
In this work, we provide a comprehensive evaluation of efficiency for MT evaluation metrics.
Towards Explainable Evaluation Metrics for Natural Language Generation
We also provide a synthesizing overview over recent approaches for explainable machine translation metrics and discuss how they relate to those goals and properties.
