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Found 5 papers, 1 papers with code
Leveraging Language Models to Detect Greenwashing
Our primary contributions encompass: developing a mathematical formulation to quantify greenwashing risk, a fine-tuned ClimateBERT model for this problem, and a comparative analysis of results.
Topic Segmentation of Semi-Structured and Unstructured Conversational Datasets using Language Models
However, current works on topic segmentation often focus on segmentation of structured texts.
On Surgical Fine-tuning for Language Encoders
We show evidence that for different downstream language tasks, fine-tuning only a subset of layers is sufficient to obtain performance that is close to and often better than fine-tuning all the layers in the language encoder.
Topic Segmentation in the Wild: Towards Segmentation of Semi-structured & Unstructured Chats
Breaking down a document or a conversation into multiple contiguous segments based on its semantic structure is an important and challenging problem in NLP, which can assist many downstream tasks.
Reconstruction of Long-Term Historical Demand Data
Long-term planning of a robust power system requires the understanding of changing demand patterns.
