Ruiqi Zhong

According to our database1, Ruiqi Zhong authored at least 25 papers between 2018 and 2023.

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Bibliography

2023
Describing Differences in Image Sets with Natural Language.
CoRR, 2023

Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations.
CoRR, 2023

Goal Driven Discovery of Distributional Differences via Language Descriptions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation.
Proceedings of the International Conference on Machine Learning, 2023

InCoder: A Generative Model for Code Infilling and Synthesis.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Goal-Driven Explainable Clustering via Language Descriptions.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
Learning by Distilling Context.
CoRR, 2022

Active Programming by Example with a Natural Language Prior.
CoRR, 2022

Summarizing Differences between Text Distributions with Natural Language.
CoRR, 2022

Describing Differences between Text Distributions with Natural Language.
Proceedings of the International Conference on Machine Learning, 2022

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Meta-learning via Language Model In-context Tuning.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
The Effect of Model Size on Worst-Group Generalization.
CoRR, 2021

Meta-tuning Language Models to Answer Prompts Better.
CoRR, 2021

Approximating How Single Head Attention Learns.
CoRR, 2021

Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Semantic Evaluation for Text-to-SQL with Distilled Test Suites.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Semantic Scaffolds for Pseudocode-to-Code Generation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Fine-grained Sentiment Analysis with Faithful Attention.
CoRR, 2019

Detecting and Reducing Bias in a High Stakes Domain.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Subspace Embedding and Linear Regression with Orlicz Norm.
Proceedings of the 35th International Conference on Machine Learning, 2018

Detecting Gang-Involved Escalation on Social Media Using Context.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018


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