ESGLens applies RAG and LLM embeddings to extract GRI-aligned information from ESG reports and achieves 0.48 Pearson correlation when regressing environmental scores on 300 company reports.
ISBN 979-8-89176-332-6
2 Pith papers cite this work. Polarity classification is still indexing.
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ESG-adapted versions of Qwen-3-4B using LoRA and IRM outperform the base model and Llama-3/Gemma-3 baselines on generative ESG question-answering tasks.
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ESGLens: An LLM-Based RAG Framework for Interactive ESG Report Analysis and Score Prediction
ESGLens applies RAG and LLM embeddings to extract GRI-aligned information from ESG reports and achieves 0.48 Pearson correlation when regressing environmental scores on 300 company reports.
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Developing an ESG-Oriented Large Language Model through ESG Practices
ESG-adapted versions of Qwen-3-4B using LoRA and IRM outperform the base model and Llama-3/Gemma-3 baselines on generative ESG question-answering tasks.