3 citations · 4 across the 5 of their papers we have counts for
5 papers
Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models
Litton Jose Kurisinkel, Pruthwik Mishra, Yue Zhang
Time series models, typically trained on numerical data, are designed to forecast future values. These models often rely on weighted averaging techniques over time intervals. Howev…
Controllable Multi-document Summarization: Coverage & Coherence Intuitive Policy with Large Language Model Based Rewards
Litton J Kurisinkel, Nancy F chen
Memory-efficient large language models are good at refining text input for better readability. However, controllability is a matter of concern when it comes to text generation task…
LLM Based Multi-Document Summarization Exploiting Main-Event Biased Monotone Submodular Content Extraction
Litton J Kurisinkel, Nancy F. Chen
Multi-document summarization is a challenging task due to its inherent subjective bias, highlighted by the low inter-annotator ROUGE-1 score of 0.4 among DUC-2004 reference summari…
Attention-based Neural Text Segmentation
Pinkesh Badjatiya, Litton J Kurisinkel, Manish Gupta +1
Text segmentation plays an important role in various Natural Language Processing (NLP) tasks like summarization, context understanding, document indexing and document noise removal…
Arithmetic Word Problem Solver using Frame Identification
Pruthwik Mishra, Litton J Kurisinkel, Dipti Misra Sharma
Automatic Word problem solving has always posed a great challenge for the NLP community. Usually a word problem is a narrative comprising of a few sentences and a question is asked…