Calculating ROUGE score between two files (line-by-line)
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Updated
Jul 8, 2021 - Perl
Calculating ROUGE score between two files (line-by-line)
Python ROUGE Score Implementation for Chinese Language Task (official rouge score)
An implementation of ROUGE family metrics for automatic summarization.
A Python wrapper of the official ROUGE-1.5.5.pl script and a re-implementation of full ROUGE metrics.
Finetune GPT2 for text summarization
ROUGE L metric implementation using tensorflow ops
Calculating ROUGE score for Korean (Wrapper for ROUGE-1.5.5.pl script)
Python implementation for evaluating summarization by ROUGE package
Python ROUGE implementation 🦁
A model inspired from the famous Show and Tell Model is implemented for automatic image captioning.
A benchmark of ChatGPT and some of its challengers on summarization task
This repository explores the use of advanced sequence-to-sequence networks and transformer models, such as BERT, BART, PEGASUS, and T5, for summarizing multi-text documents in the medical domain. It leverages extensive datasets like CORD-19 and a Biomedical Abstracts dataset from Hugging Face to fine-tune these models.
A library for evaluating Retrieval-Augmented Generation (RAG) systems
Unsupervised approach for inducing dialogue schemas from domain-specific conversations. This repository houses the source code and research findings from the application of cutting-edge NLP and ML techniques to dialogue systems.
Construction of a model to determine whether summaries of some news article were written by humans or machine generated.
The work presented was developed during the internship, as researchers in the field of Natural Language Generation, at the Insid&s Lab laboratory in Milan-Bicocca. The work carried out deals with the creation of a framework for the correct assessment of the impact of the quality of the input datasets on the quality of the text generated by the N…
This Python package is used for calculating ROUGE scores and supports over 100 languages by utilizing a multilingual BPE tokenizer. It leverages the mBERT tokenizer and was developed to support our work XL-HeadTags.
Study Uses LLMs to craft accurate, engaging headlines from Reddit Posts
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