Kurt Shuster

Wizard of Wikipedia: Knowledge-Powered Conversational agents

2018 · arXiv (Cornell University)

In open-domain dialogue intelligent agents should exhibit the use of knowledge, however there are few convincing demonstrations of this to date. The most popular sequence to sequence models typically "generate and hope" generic utterances that …

Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring

2020 · International Conference on Learning Representations

The use of deep pre-trained transformers has led to remarkable progress in a number of applications (Devlin et al., 2018). For tasks that make pairwise comparisons between sequences, matching a given input with a corresponding …

Retrieval Augmentation Reduces Hallucination in Conversation

2021

Despite showing increasingly human-like conversational abilities, state-of-the-art dialogue models often suffer from factual incorrectness and hallucination of knowledge (Roller et al., 2020). In this work we explore the use of neural-retrieval-in-the-loop architectures - recently shown …

Analysing Off-The-Shelf Options for Question Answering with Portuguese FAQs

2022 · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

Following the current interest in developing automatic question answering systems, we analyse alternative approaches for finding suitable answers from a list of Frequently Asked Questions (FAQs), in Portuguese. These rely on different technologies, some more …

OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization

2022 · arXiv (Cornell University)

Recent work has shown that fine-tuning large pre-trained language models on a collection of tasks described via instructions, a.k.a. instruction-tuning, improves their zero and few-shot generalization to unseen tasks. However, there is a limited understanding …