Albert Webson

According to our database1, Albert Webson authored at least 19 papers between 2020 and 2024.

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Bibliography

2024
Evaluating Frontier Models for Dangerous Capabilities.
CoRR, 2024

Towards Conversational Diagnostic AI.
CoRR, 2024

2023
Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models.
IEEE Trans. Vis. Comput. Graph., 2023

In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax.
CoRR, 2023

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts.
CoRR, 2023

Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs.
CoRR, 2023

Larger language models do in-context learning differently.
CoRR, 2023

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning.
Proceedings of the International Conference on Machine Learning, 2023

Are Language Models Worse than Humans at Following Prompts? It's Complicated.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Crosslingual Generalization through Multitask Finetuning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.
CoRR, 2022

Scaling Instruction-Finetuned Language Models.
CoRR, 2022

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts.
CoRR, 2022

Do Prompt-Based Models Really Understand the Meaning of Their Prompts?
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022



2021
Multitask Prompted Training Enables Zero-Shot Task Generalization.
CoRR, 2021

2020
Are "Undocumented Workers" the Same as "Illegal Aliens"? Disentangling Denotation and Connotation in Vector Spaces.
CoRR, 2020

Do "Undocumented Workers" == "Illegal Aliens"? Differentiating Denotation and Connotation in Vector Spaces.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020


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