14.5k citations · 22.4k across the 46 of their papers we have counts for
5 papers · 1 filter
The Stack: 3 TB of permissively licensed source code
Denis Kocetkov, Raymond Li, Loubna Ben Allal +10
Large Language Models (LLMs) play an ever-increasing role in the field of Artificial Intelligence (AI)--not only for natural language processing but also for code understanding and…
On the Compositional Generalization Gap of In-Context Learning
Arian Hosseini, Ankit Vani, Dzmitry Bahdanau +2
Pretrained large generative language models have shown great performance on many tasks, but exhibit low compositional generalization abilities. Scaling such models has been shown t…
LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic Parsing
Dora Jambor, Dzmitry Bahdanau
Semantic parsing is the task of producing structured meaning representations for natural language sentences. Recent research has pointed out that the commonly-used sequence-to-sequ…
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models
Gaurav Sahu, Pau Rodriguez, Issam H. Laradji +3
Data augmentation is a widely employed technique to alleviate the problem of data scarcity. In this work, we propose a prompting-based approach to generate labelled training data f…
Evaluating the Text-to-SQL Capabilities of Large Language Models
Nitarshan Rajkumar, Raymond Li, Dzmitry Bahdanau
We perform an empirical evaluation of Text-to-SQL capabilities of the Codex language model. We find that, without any finetuning, Codex is a strong baseline on the Spider benchmark…