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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
Python implementation for evaluating summarization by ROUGE package
A model inspired from the famous Show and Tell Model is implemented for automatic image captioning.
A library for evaluating Retrieval-Augmented Generation (RAG) systems
A benchmark of ChatGPT and some of its challengers on summarization task
Python ROUGE implementation 🦁
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.
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.
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 NLG models, specifically: Creation of the "Concept-Based" and "Entity-Based" versions of the WebNLG dataset; Evaluation of the quality of the datasets created; Training of LSTM and Transformer models using the OpenNMT tool; Natural language text generation by LSTM and Transformer models; Evaluation of the quality of the text generated by the NLG models; Final analysis.
Construction of a model to determine whether summaries of some news article were written by humans or machine generated.
Houses the final project for Deep Learning (DS6050), University of Virginia
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.
Automatic text summarization of news articles
This project leverages FLAN-T5 from Hugging Face to perform dialogue summarization, fine-tuning with ROUGE, and detoxifying summaries using PPO and PEFT.
Study Uses LLMs to craft accurate, engaging headlines from Reddit Posts
The results of toy example summaries and DUC corpus evaluated with different python libraries based on ROUGE metric
This repository contains a detailed implementation of a Retrieval-Augmented Generation (RAG) model leveraging Azure and Azure OpenAI services.
First Use of Rouge 1.5.5 / pyrouge in Python
Fine-tuning GPT-3.5 and Llama3 LLMs for enhanced persona consistency in chatbots using Google's Synthetic Persona Chat dataset
Collection of codes of Natural Language Processing college course