Xinyi Wang

Affiliations:
  • University of California, Department of Computer Science, Santa Barbara, CA, USA


According to our database1, Xinyi Wang authored at least 25 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Survey on Data Selection for Language Models.
Trans. Mach. Learn. Res., 2024

Automatically Correcting Large Language Models: <i>Surveying the Landscape of Diverse Automated Correction Strategies</i>.
Trans. Assoc. Comput. Linguistics, 2024

Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models.
CoRR, 2024

Gödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement.
CoRR, 2024

Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data.
CoRR, 2024

T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback.
CoRR, 2024

Position: AI/ML Influencers Have a Place in the Academic Process.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.
Trans. Mach. Learn. Res., 2023

Guiding Language Model Reasoning with Planning Tokens.
CoRR, 2023

Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies.
CoRR, 2023

Large Language Models Are Implicitly Topic Models: Explaining and Finding Good Demonstrations for In-Context Learning.
CoRR, 2023

Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Balancing for Domain Generalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Collaborative Generative AI: Integrating GPT-k for Efficient Editing in Text-to-Image Generation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

TheoremQA: A Theorem-driven Question Answering Dataset.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2021
Automatically Identifying Semantic Bias in Crowdsourced Natural Language Inference Datasets.
CoRR, 2021

Dimensions of Transparency in NLP Applications.
CoRR, 2021

Counterfactual Maximum Likelihood Estimation for Training Deep Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Dataset for Answering Time-Sensitive Questions.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

RefBERT: Compressing BERT by Referencing to Pre-computed Representations.
Proceedings of the International Joint Conference on Neural Networks, 2021

Modeling Disclosive Transparency in NLP Application Descriptions.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
Neural Topic Model with Attention for Supervised Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020


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