44 citations · 63 across the 14 of their papers we have counts for
5 papers · 1 filter
Beyond End-to-End VLMs: Leveraging Intermediate Text Representations for Superior Flowchart Understanding
Junyi Ye, Ankan Dash, Wenpeng Yin +1
Flowcharts are typically presented as images, driving the trend of using vision-language models (VLMs) for end-to-end flowchart understanding. However, two key challenges arise: (i…
Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical Problems
Junyi Ye, Jingyi Gu, Xinyun Zhao +2
The mathematical capabilities of AI systems are complex and multifaceted. Most existing research has predominantly focused on the correctness of AI-generated solutions to mathemati…
From Blind Solvers to Logical Thinkers: Benchmarking LLMs' Logical Integrity on Faulty Mathematical Problems
A M Muntasir Rahman, Junyi Ye, Wei Yao +5
Consider the math problem: "Lily received 3 cookies from her best friend yesterday and ate 5 for breakfast. Today, her friend gave her 3 more cookies. How many cookies does Lily ha…
From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing
Junyi Ye, Bhaskar Goswami, Jingyi Gu +2
This paper comprehensively reviews the application of machine learning (ML) and AI in finance, specifically in the context of asset pricing. It starts by summarizing the traditiona…
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure
Junyi Ye, Mengnan Du, Guiling Wang
This paper introduces DataFrame question answering (QA), a novel task that utilizes large language models (LLMs) to generate Pandas queries for information retrieval and data analy…