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.
To appear in Proceedings of the 33rd ACM International Conference on Multimedia (MM ’25), Dublin, Ireland
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.