Obserwuj
Yixin Nie
Tytuł
Cytowane przez
Cytowane przez
Rok
Adversarial NLI: A new benchmark for natural language understanding
Y Nie, A Williams, E Dinan, M Bansal, J Weston, D Kiela
arXiv preprint arXiv:1910.14599, 2019
4262019
Combining Fact Extraction and Verification with Neural Semantic Matching Networks
Y Nie, H Chen, M Bansal
AAAI 2019, arXiv preprint:1811.07039, 2018
2342018
Shortcut-stacked sentence encoders for multi-domain inference
Y Nie, M Bansal
EMNLP 2017 RepEval Workshop, 2017
1432017
Dynabench: Rethinking benchmarking in NLP
D Kiela, M Bartolo, Y Nie, D Kaushik, A Geiger, Z Wu, B Vidgen, G Prasad, ...
arXiv preprint arXiv:2104.14337, 2021
1362021
Revealing the importance of semantic retrieval for machine reading at scale
Y Nie, S Wang, M Bansal
arXiv preprint arXiv:1909.08041, 2019
1062019
Analyzing Compositionality-Sensitivity of NLI Models
Y Nie, Y Wang, M Bansal
AAAI 2019, arXiv preprint:1811.07033, 2018
702018
I like fish, especially dolphins: Addressing contradictions in dialogue modeling
Y Nie, M Williamson, M Bansal, D Kiela, J Weston
arXiv preprint arXiv:2012.13391, 2020
422020
What can we learn from collective human opinions on natural language inference data?
Y Nie, X Zhou, M Bansal
arXiv preprint arXiv:2010.03532, 2020
412020
The curse of performance instability in analysis datasets: Consequences, source, and suggestions
X Zhou, Y Nie, H Tan, M Bansal
arXiv preprint arXiv:2004.13606, 2020
302020
ConjNLI: Natural language inference over conjunctive sentences
S Saha, Y Nie, M Bansal
arXiv preprint arXiv:2010.10418, 2020
212020
To what extent do human explanations of model behavior align with actual model behavior?
G Prasad, Y Nie, M Bansal, R Jia, D Kiela, A Williams
arXiv preprint arXiv:2012.13354, 2020
162020
Simple compounded-label training for fact extraction and verification
Y Nie, L Bauer, M Bansal
Proceedings of the Third Workshop on Fact Extraction and VERification (FEVER …, 2020
82020
Distributed NLI: learning to predict human opinion distributions for language reasoning
X Zhou, Y Nie, M Bansal
arXiv preprint arXiv:2104.08676, 2021
62021
Mlp architectures for vision-and-language modeling: An empirical study
Y Nie, L Li, Z Gan, S Wang, C Zhu, M Zeng, Z Liu, M Bansal, L Wang
arXiv preprint arXiv:2112.04453, 2021
52021
Investigating transfer learning in multilingual pre-trained language models through Chinese natural language inference
H Hu, H Zhou, Z Tian, Y Zhang, Y Ma, Y Li, Y Nie, K Richardson
arXiv preprint arXiv:2106.03983, 2021
42021
TVLT: Textless Vision-Language Transformer
Z Tang, J Cho, Y Nie, M Bansal
arXiv preprint arXiv:2209.14156, 2022
32022
Data-Driven Natural Language Inference
Y Nie
The University of North Carolina at Chapel Hill, 2022
2022
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–17