Chenglei Si
Chenglei Si
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Bloom: A 176b-parameter open-access multilingual language model
T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
Prompting gpt-3 to be reliable
C Si, Z Gan, Z Yang, S Wang, J Wang, J Boyd-Graber, L Wang
arXiv preprint arXiv:2210.09150, 2022
Between words and characters: A brief history of open-vocabulary modeling and tokenization in NLP
SJ Mielke, Z Alyafeai, E Salesky, C Raffel, M Dey, M Gallé, A Raja, C Si, ...
arXiv preprint arXiv:2112.10508, 2021
Better robustness by more coverage: Adversarial and mixup data augmentation for robust finetuning
C Si, Z Zhang, F Qi, Z Liu, Y Wang, Q Liu, M Sun
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 …, 2021
CharBERT: Character-aware pre-trained language model
W Ma, Y Cui, C Si, T Liu, S Wang, G Hu
arXiv preprint arXiv:2011.01513, 2020
What does bert learn from multiple-choice reading comprehension datasets?
C Si, S Wang, MY Kan, J Jiang
arXiv preprint arXiv:1910.12391, 2019
Benchmarking robustness of machine reading comprehension models
C Si, Z Yang, Y Cui, W Ma, T Liu, S Wang
arXiv preprint arXiv:2004.14004, 2020
Measuring inductive biases of in-context learning with underspecified demonstrations
C Si, D Friedman, N Joshi, S Feng, D Chen, H He
arXiv preprint arXiv:2305.13299, 2023
Re-examining calibration: The case of question answering
C Si, C Zhao, S Min, J Boyd-Graber
arXiv preprint arXiv:2205.12507, 2022
What's in a name? answer equivalence for open-domain question answering
C Si, C Zhao, J Boyd-Graber
arXiv preprint arXiv:2109.05289, 2021
Sentiment aware neural machine translation
C Si, K Wu, A Aw, MY Kan
Proceedings of the 6th Workshop on Asian Translation, 200-206, 2019
Sub-character tokenization for Chinese pretrained language models
C Si, Z Zhang, Y Chen, F Qi, X Wang, Z Liu, Y Wang, Q Liu, M Sun
Transactions of the Association for Computational Linguistics 11, 469-487, 2023
Ignore this title and HackAPrompt: Exposing systemic vulnerabilities of LLMs through a global prompt hacking competition
S Schulhoff, J Pinto, A Khan, LF Bouchard, C Si, S Anati, V Tagliabue, ...
Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023
Dataset mention extraction and classification
A Prasad, C Si, MY Kan
Proceedings of the Workshop on Extracting Structured Knowledge from …, 2019
Large Language Models Help Humans Verify Truthfulness--Except When They Are Convincingly Wrong
C Si, N Goyal, ST Wu, C Zhao, S Feng, H Daumé III, J Boyd-Graber
arXiv preprint arXiv:2310.12558, 2023
Design2Code: How Far Are We From Automating Front-End Engineering?
C Si, Y Zhang, Z Yang, R Liu, D Yang
arXiv preprint arXiv:2403.03163, 2024
Getting more out of mixture of language model reasoning experts
C Si, W Shi, C Zhao, L Zettlemoyer, J Boyd-Graber
arXiv preprint arXiv:2305.14628, 2023
Best practices and lessons learned on synthetic data for language models
R Liu, J Wei, F Liu, C Si, Y Zhang, J Rao, S Zheng, D Peng, D Yang, ...
arXiv preprint arXiv:2404.07503, 2024
The Prompt Report: A Systematic Survey of Prompting Techniques
S Schulhoff, M Ilie, N Balepur, K Kahadze, A Liu, C Si, Y Li, A Gupta, ...
arXiv preprint arXiv:2406.06608, 2024
READIN: A Chinese multi-task benchmark with realistic and diverse input noises
C Si, Z Zhang, Y Chen, X Wang, Z Liu, M Sun
arXiv preprint arXiv:2302.07324, 2023
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