| Incoder: A generative model for code infilling and synthesis D Fried, A Aghajanyan, J Lin, S Wang, E Wallace, F Shi, R Zhong, W Yih, ... arXiv preprint arXiv:2204.05999, 2022 | 182 | 2022 |
| Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections R Zhong, K Lee, Z Zhang, D Klein EMNLP 2021, Findings, 2021 | 104 | 2021 |
| Unifiedskg: Unifying and multi-tasking structured knowledge grounding with text-to-text language models T Xie, CH Wu, P Shi, R Zhong, T Scholak, M Yasunaga, CS Wu, M Zhong, ... arXiv preprint arXiv:2201.05966, 2022 | 89 | 2022 |
| Fine-grained sentiment analysis with faithful attention R Zhong, S Shao, K McKeown arXiv preprint arXiv:1908.06870, 2019 | 45 | 2019 |
| Semantic evaluation for text-to-sql with distilled test suites R Zhong, T Yu, D Klein EMNLP 2020, 2020 | 44 | 2020 |
| Meta-learning via language model in-context tuning Y Chen, R Zhong, S Zha, G Karypis, H He arXiv preprint arXiv:2110.07814, 2021 | 43 | 2021 |
| Subspace embedding and linear regression with Orlicz norm A Andoni, C Lin, Y Sheng, P Zhong, R Zhong International Conference on Machine Learning, 224-233, 2018 | 33 | 2018 |
| Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level R Zhong, D Ghosh, D Klein, J Steinhardt ACL 2021, Findings, 2021 | 32 | 2021 |
| DS-1000: A natural and reliable benchmark for data science code generation Y Lai, C Li, Y Wang, T Zhang, R Zhong, L Zettlemoyer, W Yih, D Fried, ... International Conference on Machine Learning, 18319-18345, 2023 | 25 | 2023 |
| Detecting gang-involved escalation on social media using context S Chang, R Zhong, E Adams, FT Lee, S Varia, D Patton, W Frey, C Kedzie, ... EMNLP 2018, 2018 | 19 | 2018 |
| Approximating how single head attention learns C Snell, R Zhong, D Klein, J Steinhardt arXiv preprint arXiv:2103.07601, 2021 | 18 | 2021 |
| Semantic scaffolds for pseudocode-to-code generation R Zhong, M Stern, D Klein ACL 2020, 2020 | 14 | 2020 |
| Learning by distilling context C Snell, D Klein, R Zhong arXiv preprint arXiv:2209.15189, 2022 | 13 | 2022 |
| GAIA-A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System. T Zhang, A Subburathinam, G Shi, L Huang, D Lu, X Pan, M Li, B Zhang, ... TAC 2, 3, 2018 | 13 | 2018 |
| Describing differences between text distributions with natural language R Zhong, C Snell, D Klein, J Steinhardt International Conference on Machine Learning, 27099-27116, 2022 | 11* | 2022 |
| Goal driven discovery of distributional differences via language descriptions R Zhong, P Zhang, S Li, J Ahn, D Klein, J Steinhardt arXiv preprint arXiv:2302.14233, 2023 | 5 | 2023 |
| Active programming by example with a natural language prior R Zhong, C Snell, D Klein, J Eisner arXiv preprint arXiv:2205.12422, 2022 | 3 | 2022 |
| The effect of model size on worst-group generalization A Pham, E Chan, V Srivatsa, D Ghosh, Y Yang, Y Yu, R Zhong, ... arXiv preprint arXiv:2112.04094, 2021 | 3 | 2021 |
| Detecting and reducing bias in a high stakes domain R Zhong, Y Chen, D Patton, C Selous, K McKeown EMNLP 2019, 2019 | 3 | 2019 |
| Goal-Driven Explainable Clustering via Language Descriptions Z Wang, J Shang, R Zhong arXiv preprint arXiv:2305.13749, 2023 | 2 | 2023 |
Jacob SteinhardtStanford UniversityVerified email at cs.stanford.edu
