Search Results for author:
Found 10 papers, 5 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.
BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational Algebra
Many existing end-to-end systems for hybrid question answering tasks can often be boiled down to a "prompt-and-pray" paradigm, where the user has limited control and insight into the intermediate reasoning steps used to achieve the final result.
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.
Self-training Strategies for Sentiment Analysis: An Empirical Study
Self-training has recently emerged as an economical and efficient technique for developing sentiment analysis models by leveraging a small amount of labeled data and a large amount of unlabeled data.
Correcting Semantic Parses with Natural Language through Dynamic Schema Encoding
In addressing the task of converting natural language to SQL queries, there are several semantic and syntactic challenges.
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.
CEREC: A Corpus for Entity Resolution in Email Conversations
We present the first large scale corpus for entity resolution in email conversations (CEREC).
Joint Learning of Syntactic Features Helps Discourse Segmentation
This paper describes an accurate framework for carrying out multi-lingual discourse segmentation with BERT (Devlin et al., 2019).
A Study on Entity Resolution for Email Conversations
This paper investigates the problem of entity resolution for email conversations and presents a seed annotated corpus of email threads labeled with entity coreference chains.
