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Joe Stacey
Joe Stacey
Verified email at imperial.ac.uk
Title
Cited by
Cited by
Year
Supervising Model Attention with Human Explanations for Robust Natural Language Inference
J Stacey, Y Belinkov, M Rei
AAAI 2022, 2022
57*2022
Avoiding the hypothesis-only bias in natural language inference via ensemble adversarial training
J Stacey, P Minervini, H Dubossarsky, S Riedel, T Rocktäschel
EMNLP 2020, 2020
49*2020
Logical Reasoning with Span-Level Predictions for Interpretable and Robust NLI Models
J Stacey, P Minervini, H Dubossarsky, M Rei
EMNLP 2022, 2022
15*2022
Logical reasoning for natural language inference using generated facts as atoms
J Stacey, P Minervini, H Dubossarsky, OM Camburu, M Rei
arXiv preprint arXiv:2305.13214, 2023
62023
Distilling Robustness into Natural Language Inference Models with Domain-Targeted Augmentation
J Stacey, M Rei
ACL Findings 2024, 2023
4*2023
When and Why Does Bias Mitigation Work?
A Ravichander, J Stacey, M Rei
Findings of the Association for Computational Linguistics: EMNLP 2023, 9233-9247, 2023
22023
LUCID: LLM-Generated Utterances for Complex and Interesting Dialogues
J Stacey, J Cheng, J Torr, T Guigue, J Driesen, A Coca, M Gaynor, ...
NAACL SRW 2024, 2024
12024
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Articles 1–7