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Deep transfer learning & beyond: Transformer language models in information systems research
R Gruetzemacher, D Paradice - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
AI is widely thought to be poised to transform business, yet current perceptions of the scope
of this transformation may be myopic. Recent progress in natural language processing …
of this transformation may be myopic. Recent progress in natural language processing …
A holistic approach to undesired content detection in the real world
We present a holistic approach to building a robust and useful natural language
classification system for real-world content moderation. The success of such a system relies …
classification system for real-world content moderation. The success of such a system relies …
Finetuned language models are zero-shot learners
This paper explores a simple method for improving the zero-shot learning abilities of
language models. We show that instruction tuning--finetuning language models on a …
language models. We show that instruction tuning--finetuning language models on a …
Generating training data with language models: Towards zero-shot language understanding
Pretrained language models (PLMs) have demonstrated remarkable performance in various
natural language processing tasks: Unidirectional PLMs (eg, GPT) are well known for their …
natural language processing tasks: Unidirectional PLMs (eg, GPT) are well known for their …
Leveraging large language models in conversational recommender systems
L Friedman, S Ahuja, D Allen, Z Tan… - arxiv preprint arxiv …, 2023 - arxiv.org
A Conversational Recommender System (CRS) offers increased transparency and control to
users by enabling them to engage with the system through a real-time multi-turn dialogue …
users by enabling them to engage with the system through a real-time multi-turn dialogue …