Shane Storks

Orcid: 0000-0002-5826-4426

According to our database1, Shane Storks authored at least 12 papers between 2019 and 2024.

Collaborative distances:

Timeline

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2024
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PhD thesis 
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Links

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Bibliography

2024
Explainable Procedural Mistake Detection.
CoRR, 2024

Eliciting In-Context Learning in Vision-Language Models for Videos Through Curated Data Distributional Properties.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Can Foundation Models Watch, Talk and Guide You Step by Step to Make a Cake?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

NLP Reproducibility For All: Understanding Experiences of Beginners.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

In-Context Analogical Reasoning with Pre-Trained Language Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Best of Both Worlds: A Hybrid Approach for Multi-Hop Explanation with Declarative Facts.
CoRR, 2022

DANLI: Deliberative Agent for Following Natural Language Instructions.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
Are We There Yet? Learning to Localize in Embodied Instruction Following.
CoRR, 2021

Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Beyond the Tip of the Iceberg: Assessing Coherence of Text Classifiers.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2019
Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches.
CoRR, 2019


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