17 citations · 44 across the 6 of their papers we have counts for
6 papers
CodeMirage: Hallucinations in Code Generated by Large Language Models
Vibhor Agarwal, Yulong Pei, Salwa Alamir +1
Large Language Models (LLMs) have shown promising potentials in program generation and no-code automation. However, LLMs are prone to generate hallucinations, i.e., they generate t…
BuDDIE: A Business Document Dataset for Multi-task Information Extraction
Ran Zmigrod, Dongsheng Wang, Mathieu Sibue +10
The field of visually rich document understanding (VRDU) aims to solve a multitude of well-researched NLP tasks in a multi-modal domain. Several datasets exist for research on spec…
Code Revert Prediction with Graph Neural Networks: A Case Study at J.P. Morgan Chase
Yulong Pei, Salwa Alamir, Rares Dolga +1
Code revert prediction, a specialized form of software defect detection, aims to forecast or predict the likelihood of code changes being reverted or rolled back in software develo…
DocLLM: A layout-aware generative language model for multimodal document understanding
Dongsheng Wang, Natraj Raman, Mathieu Sibue +6
Enterprise documents such as forms, invoices, receipts, reports, contracts, and other similar records, often carry rich semantics at the intersection of textual and spatial modalit…
Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams
Ethan Callanan, Amarachi Mbakwe, Antony Papadimitriou +6
Large Language Models (LLMs) have demonstrated remarkable performance on a wide range of Natural Language Processing (NLP) tasks, often matching or even beating state-of-the-art ta…
Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks
Xianzhi Li, Samuel Chan, Xiaodan Zhu +4
The most recent large language models(LLMs) such as ChatGPT and GPT-4 have shown exceptional capabilities of generalist models, achieving state-of-the-art performance on a wide ran…