158 citations · 163 across the 6 of their papers we have counts for
6 papers
GOLD: Generalized Knowledge Distillation via Out-of-Distribution-Guided Language Data Generation
Mohsen Gholami, Mohammad Akbari, Cindy Hu +3
Knowledge distillation from LLMs is essential for the efficient deployment of language models. Prior works have proposed data generation using LLMs for preparing distilled models.…
SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network
Lei Yao, Yong Zhang, Zilong Yan +1
In the rapid development of artificial intelligence, solving complex AI tasks is a crucial technology in intelligent mobile networks. Despite the good performance of specialized AI…
Revealing Unfair Models by Mining Interpretable Evidence
Mohit Bajaj, Lingyang Chu, Vittorio Romaniello +5
The popularity of machine learning has increased the risk of unfair models getting deployed in high-stake applications, such as justice system, drug/vaccination design, and medical…
ML4CO: Is GCNN All You Need? Graph Convolutional Neural Networks Produce Strong Baselines For Combinatorial Optimization Problems, If Tuned and Trained Properly, on Appropriate Data
Amin Banitalebi-Dehkordi, Yong Zhang
The 2021 NeurIPS Machine Learning for Combinatorial Optimization (ML4CO) competition was designed with the goal of improving state-of-the-art combinatorial optimization solvers by…
Mining Minority-class Examples With Uncertainty Estimates
Gursimran Singh, Lingyang Chu, Lanjun Wang +3
In the real world, the frequency of occurrence of objects is naturally skewed forming long-tail class distributions, which results in poor performance on the statistically rare cla…
A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method
Sen Zhao, Yong Zhang, Shang Wang +2
Data-driven methods for remaining useful life (RUL) prediction normally learn features from a fixed window size of a priori of degradation, which may lead to less accurate predicti…