Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …

While recent language models have the ability to take long contexts as input, relatively little
is known about how well they use longer context. We analyze the performance of language …

Retrieval-Augmented Generation (RAG) has recently emerged as a method to extend
beyond the pre-trained knowledge of Large Language Models by augmenting the original …

GPT-3 can perform numerous tasks when provided a natural language prompt that contains
a few training examples. We show that this type of few-shot learning can be unstable: the …

Abstract “Knowledge tracing (KT)” is an emerging and popular research topic in the field of
online education that seeks to assess students' mastery of a concept based on their …

Time series forecasting is an important problem across many domains, including predictions
of solar plant energy output, electricity consumption, and traffic jam situation. In this paper …

Large pre-trained neural networks such as BERT have had great recent success in NLP,
motivating a growing body of research investigating what aspects of language they are able …

Abstract We introduce the Block-Recurrent Transformer, which applies a transformer layer in
a recurrent fashion along a sequence, and has linear complexity with respect to sequence …

In the field of artificial intelligence, a combination of scale in data and model capacity
enabled by unsupervised learning has led to major advances in representation learning and …