3 accepted papers
Enriching sentences with knowledge from qualitative sources benefits various NLP tasks and enhances the use of labeled data in model training. This is crucial for Financial Sentiment Analysis (FSA), where texts are often brief and contain implied information. We introduce RE-FIN (Retrieval-based Enr…
Despite the state-of-the-art performance of Large Language Models (LLMs), these models often suffer from hallucinations, which can undermine their performance in critical applications. In this work, we propose SAFE, a novel framework for detecting and mitigating hallucinations by leveraging Sparse A
In recent years, vector representations of words have proven to be extremely useful across a wide range of NLP applications. Because of the broad interest in the topic, it became essential to answer the following question: is it possible to align different embeddings, in order to compare terms belon…