Jun Yan

Can Machines Intelligently Propose Novel and Reasonable Scientific Hypotheses?

2017

Machine intelligence is attracting increasing attention from both industry and academia. However, the problem of how to make machines innovate novel hypothesis is underexplored. Automatic hypothesis generation can effectively shorten research process. In this work, …

An CNN-LSTM Attention Approach to Understanding User Query Intent from Online Health Communities

2017

Understanding user query intent is a crucial task to Question-Answering area. With the development of online health services, online health communities generate huge amount of valuable medical Question-Answering data, where user intention can be mined. …

Influence of vapor-phase fluids on the geochemical characterization of hydrothermal sulfides in the shimmering waters of the southern Okinawa Trough

2021 · Ore Geology Reviews

Inverted lakes filled with shimmering water are unique environments within hydrothermal systems. Recently, vapor-phase fluids have been detected on the top of an inverted lake in a mushroom cap-shaped (MC) sulfide structure based on in …

Density-Aware Hyper-Graph Neural Networks for Graph-based Semi-supervised Node Classification

2022 · arXiv (Cornell University)

Graph-based semi-supervised learning, which can exploit the connectivity relationship between labeled and unlabeled data, has been shown to outperform the state-of-the-art in many artificial intelligence applications. One of the most challenging problems for graph-based semi-supervised …

On the Robustness of Reading Comprehension Models to Entity Renaming

2021 · arXiv (Cornell University)

We study the robustness of machine reading comprehension (MRC) models to entity renaming -- do models make more wrong predictions when the same questions are asked about an entity whose name has been changed? Such …

Distributed Interaction Graph Construction for Dynamic DCOPs in Cooperative Multi-agent Systems

2022 · arXiv (Cornell University)

DCOP algorithms usually rely on interaction graphs to operate. In open and dynamic environments, such methods need to address how this interaction graph is generated and maintained among agents. Existing methods require reconstructing the entire …

Detecting Memory Errors in Python Native Code by Tracking Object Lifecycle with Reference Count

2023

Third-party Python modules are usually implemented as binary extensions by using native code (C/C++) to provide additional features and runtime acceleration. In native code, the heap-allocated PyObjects are managed by the reference counting mechanism provided …