Augmented Language Models (ALMs) empower large language models with the
...
Current disfluency detection models focus on individual utterances each ...
While various AI explanation (XAI) methods have been proposed to interpr...
In recent years, Natural Language Generation (NLG) techniques in AI (e.g...
A surge of advances in language models (LMs) has led to significant inte...
Prompt tuning is a technology that tunes a small set of parameters to st...
The in-context learning capabilities of LLMs like GPT-3 allow annotators...
Real-time crowd-powered systems, such as Chorus/Evorus, VizWiz, and
Appa...
Existing self-explaining models typically favor extracting the shortest
...
Modern speaker verification models use deep neural networks to encode
ut...
We propose a class of essentially non-oscillatory schemes with adaptive ...
When constructing high-order schemes for solving hyperbolic conservation...
We propose a class of weighted compact central (WCC) schemes for solving...
It is unclear if existing interpretations of deep neural network models
...
We propose an alternative reconstruction for weighted essentially
non-os...
Explaining to users why automated systems make certain mistakes is impor...
Providing explanations for complicated deep neural network (DNN) models ...