Qinyuan Ye
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CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP
Q Ye, BY Lin, X Ren
EMNLP 2021, 2021
Refining language models with compositional explanations
H Yao, Y Chen, Q Ye, X Jin, X Ren
NeurIPS 2021, 2021
Learning from Explanations with Neural Execution Tree
Z Wang, Y Qin, W Zhou, J Yan, Q Ye, L Neves, Z Liu, X Ren
ICLR 2020, 2019
Learning to Generate Task-Specific Adapters from Task Description
Q Ye, X Ren
ACL-IJCNLP 2021 (Short Paper), 2021
Teaching Machine Comprehension with Compositional Explanations
Q Ye, X Huang, E Boschee, X Ren
Findings of EMNLP 2020, 2020
Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction
Q Ye, L Liu, M Zhang, X Ren
EMNLP-IJCNLP 2019, 2019
Semi-automated protocol disambiguation and code generation
J Yen, T Lévai, Q Ye, X Ren, R Govindan, B Raghavan
SIGCOMM 2021, 272-286, 2021
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation
DH Lee, R Khanna, BY Lin, J Chen, S Lee, Q Ye, E Boschee, L Neves, ...
ACL 2020 (Demo Track), 2020
On the Influence of Masking Policies in Intermediate Pre-training
Q Ye, BZ Li, S Wang, B Bolte, H Ma, W Yih, X Ren, M Khabsa
EMNLP 2021, 2021
Studying strategically: Learning to mask for closed-book QA
Q Ye, BZ Li, S Wang, B Bolte, H Ma, W Yih, X Ren, M Khabsa
arXiv preprint arXiv:2012.15856, 2020
Prompt engineering a prompt engineer
Q Ye, M Axmed, R Pryzant, F Khani
arXiv preprint arXiv:2311.05661, 2023
Eliciting and Understanding Cross-Task Skills with Task-Level Mixture-of-Experts
Q Ye, J Zha, X Ren
Findings of EMNLP 2022, 2022
FiD-ICL: A Fusion-in-Decoder Approach for Efficient In-Context Learning
Q Ye, I Beltagy, ME Peters, X Ren, H Hajishirzi
ACL 2023, 2022
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
Q Ye, HY Fu, X Ren, R Jia
Findings of EMNLP 2023, 2023
Estimating Large Language Model Capabilities without Labeled Test Data
HY Fu, Q Ye, A Xu, X Ren, R Jia
Findings of EMNLP 2023, 2023
Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models
Q Ye, M Khabsa, M Lewis, S Wang, X Ren, A Jaech
NAACL 2022, 2021
LLM-driven Instruction Following: Progresses and Concerns
W Yin, Q Ye, P Liu, X Ren, H Schütze
Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023
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