CodeBERTScore: an automatic metric for code generation, based on BERTScore
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Updated
Mar 1, 2024 - Jupyter Notebook
CodeBERTScore: an automatic metric for code generation, based on BERTScore
EMNLP'2022: BERTScore is Unfair: On Social Bias in Language Model-Based Metrics for Text Generation
LLM Evaluation and Observability System for Football Content
MAchine Translation Evaluation Online (MATEO)
Domain-specialized Gemma 2 27B + Gemma 4 31B for SEC filings — fine-tuned on TPU v6e-8 with PyTorch/XLA FSDPv2, plus a Vertex AI Vector Search RAG demo (69 tickers × 381 filings). Same LoRA recipe, +3.5% / +5.8% BERTScore F1.
Fine-tuning GPT-3.5 and Llama3 LLMs for enhanced persona consistency in chatbots using Google's Synthetic Persona Chat dataset
ViAG: A Novel Framework for Fine-tuning Answer Generation models ultilizing Encoder-Decoder and Decoder-only Transformers's architecture
Agent Orchestration - LLM for Legal Metadata Extraction: A Comparative Analysis of Efficiency and Precision (paper 161 PROPOR)
LLM evaluation on a 643-question Austrian tax-law benchmark: ROUGE, BLEU and BERTScore plus a manual failure-mode analysis. Compares a QLoRA fine-tuned 5B model against a 31B zero-shot baseline; the smaller fine-tuned model wins on all five metrics.
Medical Question Answering System using on PubMed dataset.
Model-agnostic toolkit to evaluate text-summarization models — ROUGE/BLEU/BERTScore + perplexity + LLM-as-judge, MLflow tracking, CLI + library with unit-tested metrics.
Implementation of a task-specific QLoRA supervised fine-tuning pipeline for LLaMA-2-7B-Chat, developed for an independent study on structured cover letter generation.
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…
[radscore] Evaluation metrics for radiology report generation — BLEU, ROUGE, BERTScore, F1-RadGraph, CheXbert F1 & GREEN in one `pip install`.
An LLM-powered application that summarizes scientific research papers, extracts tables, and provides real-time evaluation using BERTScore (F1) and ROUGE. Built using Meta’s LLaMA 3–8B via Groq, with table extraction powered by pdfplumber and pandas.
Role-aware crisis tweet summarization using transformer baselines, automated reward scoring, and preference optimization.
AI-powered research paper summarizer built with Streamlit and Google Gemini. Supports customizable summaries, paper Q&A, ROUGE/BERTScore evaluation, and latency benchmarking.
An end-to-end prompt-based navigation task for the Pioneer Valley region: synthetic data, a custom evaluation suite, and several methods helping map the problem's Pareto front
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