activity
20222025
most citedSynthetic Data Applications in Finance

8 citations · 16 across the 18 of their papers we have counts for

collaborators
Showing 2024Show all

14 papers · 1 filter

cs.AI2024★ 2 cited

LAW: Legal Agentic Workflows for Custody and Fund Services Contracts

William Watson, Nicole Cho, Nishan Srishankar +7

Legal contracts in the custody and fund services domain govern critical aspects such as key provider responsibilities, fee schedules, and indemnification rights. However, it is cha…

cs.AI2024

AdaptAgent: Adapting Multimodal Web Agents with Few-Shot Learning from Human Demonstrations

Gaurav Verma, Rachneet Kaur, Nishan Srishankar +3

State-of-the-art multimodal web agents, powered by Multimodal Large Language Models (MLLMs), can autonomously execute many web tasks by processing user instructions and interacting…

cs.LG2024

Behavioral Sequence Modeling with Ensemble Learning

Maxime Kawawa-Beaudan, Srijan Sood, Soham Palande +3

We investigate the use of sequence analysis for behavior modeling, emphasizing that sequential context often outweighs the value of aggregate features in understanding human behavi…

cs.CV2024

Shining a Light on Hurricane Damage Estimation via Nighttime Light Data: Pre-processing Matters

Nancy Thomas, Saba Rahimi, Annita Vapsi +5

Amidst escalating climate change, hurricanes are inflicting severe socioeconomic impacts, marked by heightened economic losses and increased displacement. Previous research utilize…

cs.LG2024

Auditing and Enforcing Conditional Fairness via Optimal Transport

Mohsen Ghassemi, Alan Mishler, Niccolo Dalmasso +4

Conditional demographic parity (CDP) is a measure of the demographic parity of a predictive model or decision process when conditioning on an additional feature or set of features.…

cs.LG2024

Ensemble Methods for Sequence Classification with Hidden Markov Models

Maxime Kawawa-Beaudan, Srijan Sood, Soham Palande +3

We present a lightweight approach to sequence classification using Ensemble Methods for Hidden Markov Models (HMMs). HMMs offer significant advantages in scenarios with imbalanced…

cs.CR2024★ 1 cited

Adaptive and Robust Watermark for Generative Tabular Data

Dung Daniel Ngo, Archan Ray, Akshay Seshadri +6

In recent years, watermarking generative tabular data has become a prominent framework to protect against the misuse of synthetic data. However, while most prior work in watermarki…

math.OC2024

Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls

Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi +3

Adversarially robust optimization (ARO) has emerged as the *de facto* standard for training models that hedge against adversarial attacks in the test stage. While these models are…

cs.LG2024

LETS-C: Leveraging Text Embedding for Time Series Classification

Rachneet Kaur, Zhen Zeng, Tucker Balch +1

Recent advancements in language modeling have shown promising results when applied to time series data. In particular, fine-tuning pre-trained large language models (LLMs) for time…

cs.AI2024★ 2 cited

HiddenTables & PyQTax: A Cooperative Game and Dataset For TableQA to Ensure Scale and Data Privacy Across a Myriad of Taxonomies

William Watson, Nicole Cho, Tucker Balch +1

A myriad of different Large Language Models (LLMs) face a common challenge in contextually analyzing table question-answering tasks. These challenges are engendered from (1) finite…

cs.CR2024

Six Levels of Privacy: A Framework for Financial Synthetic Data

Tucker Balch, Vamsi K. Potluru, Deepak Paramanand +1

Synthetic Data is increasingly important in financial applications. In addition to the benefits it provides, such as improved financial modeling and better testing procedures, it p…

cs.CL2024

FlowMind: Automatic Workflow Generation with LLMs

Zhen Zeng, William Watson, Nicole Cho +4

The rapidly evolving field of Robotic Process Automation (RPA) has made significant strides in automating repetitive processes, yet its effectiveness diminishes in scenarios requir…

cs.CV2024

From Pixels to Predictions: Spectrogram and Vision Transformer for Better Time Series Forecasting

Zhen Zeng, Rachneet Kaur, Suchetha Siddagangappa +2

Time series forecasting plays a crucial role in decision-making across various domains, but it presents significant challenges. Recent studies have explored image-driven approaches…

cs.LG2024★ 8 cited

Synthetic Data Applications in Finance

Vamsi K. Potluru, Daniel Borrajo, Andrea Coletta +17

Synthetic data has made tremendous strides in various commercial settings including finance, healthcare, and virtual reality. We present a broad overview of prototypical applicatio…