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Found 5 papers, 1 papers with code
Jetsons at FinNLP 2024: Towards Understanding the ESG Impact of a News Article using Transformer-based Models
For the impact type classification task, our XLM-RoBERTa model fine-tuned using a custom fine-tuning strategy ranked first for the English language.
Towards leveraging LLMs for Conditional QA
This study delves into the capabilities and limitations of Large Language Models (LLMs) in the challenging domain of conditional question-answering.
HeySQuAD: A Spoken Question Answering Dataset
Spoken question answering (SQA) systems are critical for digital assistants and other real-world use cases, but evaluating their performance is a challenge due to the importance of human-spoken questions.
Understanding BLOOM: An empirical study on diverse NLP tasks
We view the landscape of large language models (LLMs) through the lens of the recently released BLOOM model to understand the performance of BLOOM and other decoder-only LLMs compared to BERT-style encoder-only models.
On Controlled DeEntanglement for Natural Language Processing
Latest addition to the toolbox of human species is Artificial Intelligence(AI).
