most citedCodeT5+: Open Code Large Language Models for Code Understanding and Generation

28 citations · 35 across the 11 of their papers we have counts for

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cs.LG2024

Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory

Hung Le, Dung Nguyen, Kien Do +2

We propose Pointer-Augmented Neural Memory (PANM) to help neural networks understand and apply symbol processing to new, longer sequences of data. PANM integrates an external neura…

cs.LG2024

Revisiting the Dataset Bias Problem from a Statistical Perspective

Kien Do, Dung Nguyen, Hung Le +6

In this paper, we study the "dataset bias" problem from a statistical standpoint, and identify the main cause of the problem as the strong correlation between a class attribute u a…

cs.LG20231 cited

SurvTimeSurvival: Survival Analysis On The Patient With Multiple Visits/Records

Hung Le, Ong Eng-Jon, Bober Miroslaw

The accurate prediction of survival times for patients with severe diseases remains a critical challenge despite recent advances in artificial intelligence. This study introduces "…

cs.LG20231 cited

Universal Graph Continual Learning

Thanh Duc Hoang, Do Viet Tung, Duy-Hung Nguyen +3

We address catastrophic forgetting issues in graph learning as incoming data transits from one to another graph distribution. Whereas prior studies primarily tackle one setting of…

cs.LG20233 cited

BO-Muse: A human expert and AI teaming framework for accelerated experimental design

Sunil Gupta, Alistair Shilton, Arun Kumar A +7

In this paper we introduce BO-Muse, a new approach to human-AI teaming for the optimization of expensive black-box functions. Inspired by the intrinsic difficulty of extracting exp…