An Ensemble Approach to Personalized Real Time Predictive Writing for Experts

TL;DR

This paper presents an ensemble system combining large language models, Markov models, and character-level models to provide personalized, real-time predictive writing assistance for financial experts, improving efficiency and accuracy.

Contribution

It introduces a novel ensemble approach that integrates multiple machine learning techniques for personalized, low-latency predictive writing tailored to expert needs.

Findings

System saves over a million keystrokes.

Enhances writing efficiency and confidence.

Operates effectively with minimal training data.

Abstract

Completing a sentence, phrase or word after typing few words / characters is very helpful for Intuit financial experts, while taking notes or having a live chat with users, since they need to write complex financial concepts more efficiently and accurately many times in a day. In this paper, we tie together different approaches like large language models, traditional Markov Models and char level models to create an end-to-end system to provide personalised sentence/word auto-complete suggestions to experts, under strict latency constraints. Proposed system can auto-complete sentences, phrases or words while writing with personalisation and can be trained with very less data and resources with good efficiency. Our proposed system is not only efficient and personalized but also robust as it leverages multiple machine learning techniques along with transfer learning approach to fine tune large language model with Intuit specific data. This ensures that even in cases of rare or unusual phrases, the system can provide relevant auto-complete suggestions in near real time. Survey has showed that this system saves expert note-taking time and boosts expert confidence in their communication with teammates and clients. Since enabling this predictive writing feature for QBLive experts, more than a million keystrokes have been saved based on these suggestions. We have done comparative study for our ensemble choice. Moreover this feature can be integrated with any product which has writing facility within a very short period of time.