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20172023
most citedLearning with Weak Supervision for Email Intent Detection

26 citations · 102 across the 21 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CL2022★ 1 cited

Boosting Natural Language Generation from Instructions with Meta-Learning

Budhaditya Deb, Guoqing Zheng, Ahmed Hassan Awadallah

Recent work has shown that language models (LMs) trained with multi-task \textit{instructional learning} (MTIL) can solve diverse NLP tasks in zero- and few-shot settings with impr…

cs.LG2022★ 4 cited

Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity

Kaize Ding, Elnaz Nouri, Guoqing Zheng +2

The success of graph neural networks on graph-based web mining highly relies on abundant human-annotated data, which is laborious to obtain in practice. When only few labeled nodes…

cs.LG2022★ 1 cited

ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels

Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee +2

Existing works on anomaly detection (AD) rely on clean labels from human annotators that are expensive to acquire in practice. In this work, we propose a method to leverage weak/no…

cs.CL2022

Pathologies of Pre-trained Language Models in Few-shot Fine-tuning

Hanjie Chen, Guoqing Zheng, Ahmed Hassan Awadallah +1

Although adapting pre-trained language models with few examples has shown promising performance on text classification, there is a lack of understanding of where the performance ga…

cs.CL2022★ 11 cited

Knowledge Infused Decoding

Ruibo Liu, Guoqing Zheng, Shashank Gupta +5

Pre-trained language models (LMs) have been shown to memorize a substantial amount of knowledge from the pre-training corpora; however, they are still limited in recalling factuall…