48 citations · 125 across the 16 of their papers we have counts for
18 papers
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning
Tao Yang, Jinghao Deng, Xiaojun Quan +2
Fine-tuning large pre-trained language models on downstream tasks is apt to suffer from overfitting when limited training data is available. While dropout proves to be an effective…
XPrompt: Exploring the Extreme of Prompt Tuning
Fang Ma, Chen Zhang, Lei Ren +5
Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gr…
Autoregressive Entity Generation for End-to-End Task-Oriented Dialog
Guanhuan Huang, Xiaojun Quan, Qifan Wang
Task-oriented dialog (TOD) systems often require interaction with an external knowledge base to retrieve necessary entity (e.g., restaurant) information to support the response gen…
UBARv2: Towards Mitigating Exposure Bias in Task-Oriented Dialogs
Yunyi Yang, Hong Ding, Qingyi Liu +1
This paper studies the exposure bias problem in task-oriented dialog systems, where the model's generated content over multiple turns drives the dialog context away from the ground…
Deep Partial Multiplex Network Embedding
Qifan Wang, Yi Fang, Anirudh Ravula +5
Network embedding is an effective technique to learn the low-dimensional representations of nodes in networks. Real-world networks are usually with multiplex or having multi-view r…
WebFormer: The Web-page Transformer for Structure Information Extraction
Qifan Wang, Yi Fang, Anirudh Ravula +3
Structure information extraction refers to the task of extracting structured text fields from web pages, such as extracting a product offer from a shopping page including product t…