José Cambronero

According to our database, José Cambronero authored at least 37 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

PyDex: Repairing Bugs in Introductory Python Assignments using LLMs.

Jialu Zhang, José Pablo Cambronero, Sumit Gulwani, Vu Le, Ruzica Piskac, Gustavo Soares, Gust Verbruggen

Proc. ACM Program. Lang., 2024

An Empirical Study of Validating Synthetic Data for Formula Generation.

Usneek Singh, José Cambronero, Sumit Gulwani, Aditya Kanade, Anirudh Khatry, Vu Le, Mukul Singh, Gust Verbruggen

CoRR, 2024

SpreadsheetLLM: Encoding Spreadsheets for Large Language Models.

Yuzhang Tian, Jianbo Zhao, Haoyu Dong, Junyu Xiong, Shiyu Xia, Mengyu Zhou, Yun Lin, José Cambronero, Yeye He, Shi Han, Dongmei Zhang

CoRR, 2024

Solving Data-centric Tasks using Large Language Models.

Shraddha Barke, Christian Pölitz, Carina Negreanu, Benjamin Zorn, José Cambronero, Andrew D. Gordon, Vu Le, Elnaz Nouri, Nadia Polikarpova, Advait Sarkar, Brian Slininger, Neil Toronto, Jack Williams

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Automating Human Tutor-Style Programming Feedback: Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation.

Tung Phung, Victor-Alexandru Padurean, Anjali Singh, Christopher Brooks, José Cambronero, Sumit Gulwani, Adish Singla, Gustavo Soares

Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024

Encoding Spreadsheets for Large Language Models.

Haoyu Dong, Jianbo Zhao, Yuzhang Tian, Junyu Xiong, Mengyu Zhou, Yun Lin, José Cambronero, Yeye He, Shi Han, Dongmei Zhang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

EmFORE: Learning Email Folder Classification Rules by Demonstration.

Mukul Singh, Gust Verbruggen, José Cambronero, Vu Le, Sumit Gulwani

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

FLAME: A Small Language Model for Spreadsheet Formulas.

Harshit Joshi, Abishai Ebenezer, José Pablo Cambronero Sánchez, Sumit Gulwani, Aditya Kanade, Vu Le, Ivan Radicek, Gust Verbruggen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language.

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Carina Negreanu, Elnaz Nouri, Mohammad Raza, Gust Verbruggen

Proc. VLDB Endow., November, 2023

FlashFill++: Scaling Programming by Example by Cutting to the Chase.

José Cambronero, Sumit Gulwani, Vu Le, Daniel Perelman, Arjun Radhakrishna, Clint Simon, Ashish Tiwari

Proc. ACM Program. Lang., January, 2023

CORNET: Learning Spreadsheet Formatting Rules By Example.

Mukul Singh, José Pablo Cambronero Sánchez, Sumit Gulwani, Vu Le, Carina Negreanu, Gust Verbruggen

Proc. VLDB Endow., 2023

CORNET: Learning Table Formatting Rules By Example.

Mukul Singh, José Pablo Cambronero Sánchez, Sumit Gulwani, Vu Le, Carina Negreanu, Mohammad Raza, Gust Verbruggen

Proc. VLDB Endow., 2023

Assessing GPT4-V on Structured Reasoning Tasks.

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Gust Verbruggen

CoRR, 2023

Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs.

Ananya Singha, José Cambronero, Sumit Gulwani, Vu Le, Chris Parnin

CoRR, 2023

Co-audit: tools to help humans double-check AI-generated content.

Andrew D. Gordon, Carina Negreanu, José Cambronero, Rasika Chakravarthy, Ian Drosos, Hao Fang, Bhaskar Mitra, Hannah Richardson, Advait Sarkar, Stephanie Simmons, Jack Williams, Ben Zorn

CoRR, 2023

DataVinci: Learning Syntactic and Semantic String Repairs.

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Carina Negreanu, Gust Verbruggen

CoRR, 2023

Demonstration of CORNET: A System For Learning Spreadsheet Formatting Rules By Example.

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Carina Negreanu, Gust Verbruggen

CoRR, 2023

Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors.

Tung Phung, Victor-Alexandru Padurean, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares

Proceedings of the 2023 ACM Conference on International Computing Education Research, 2023

CodeFusion: A Pre-trained Diffusion Model for Code Generation.

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Carina Negreanu, Gust Verbruggen

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models.

Tung Phung, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares

Proceedings of the 16th International Conference on Educational Data Mining, 2023

EmFore: Online Learning of Email Folder Classification Rules.

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Gust Verbruggen

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Repair Is Nearly Generation: Multilingual Program Repair with LLMs.

Harshit Joshi, José Pablo Cambronero Sánchez, Sumit Gulwani, Vu Le, Gust Verbruggen, Ivan Radicek

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Neurosymbolic repair for low-code formula languages.

Rohan Bavishi, Harshit Joshi, José Cambronero, Anna Fariha, Sumit Gulwani, Vu Le, Ivan Radicek, Ashish Tiwari

Proc. ACM Program. Lang., 2022

Repairing Bugs in Python Assignments Using Large Language Models.

Jialu Zhang, José Cambronero, Sumit Gulwani, Vu Le, Ruzica Piskac, Gustavo Soares, Gust Verbruggen

CoRR, 2022

CORNET: A neurosymbolic approach to learning conditional table formatting rules by example.

Mukul Singh, José Pablo Cambronero Sánchez, Sumit Gulwani, Vu Le, Carina Negreanu, Mohammad Raza, Gust Verbruggen

CoRR, 2022

LoopStack: a Lightweight Tensor Algebra Compiler Stack.

Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather, Aleksandar Zlateski

CoRR, 2022

2021

Mining Software Artifacts for use in Automated Machine Learning.

José Pablo Cambronero Sánchez

PhD thesis, 2021

Doing More with Less: Characterizing Dataset Downsampling for AutoML.

Fatjon Zogaj, José Pablo Cambronero, Martin C. Rinard, Jürgen Cito

Proc. VLDB Endow., 2021

Searching for Replacement Classes.

Malavika Samak, José Pablo Cambronero, Martin C. Rinard

CoRR, 2021

Inferring Drop-in Binary Parsers from Program Executions.

Thurston H. Y. Dang, José Pablo Cambronero, Martin C. Rinard

CoRR, 2021

2020

AMS: generating AutoML search spaces from weak specifications.

José Pablo Cambronero, Jürgen Cito, Martin C. Rinard

Proceedings of the ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020

2019

AL: autogenerating supervised learning programs.

José Pablo Cambronero, Martin C. Rinard

Proc. ACM Program. Lang., 2019

Characterizing Developer Use of Automatically Generated Patches.

José Pablo Cambronero, Jiasi Shen, Jürgen Cito, Elena L. Glassman, Martin C. Rinard

Proceedings of the 2019 IEEE Symposium on Visual Languages and Human-Centric Computing, 2019

When deep learning met code search.

José Cambronero, Hongyu Li, Seohyun Kim, Koushik Sen, Satish Chandra

Proceedings of the ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2019

Active learning for software engineering.

José Pablo Cambronero, Thurston H. Y. Dang, Nikos Vasilakis, Jiasi Shen, Jerry Wu, Martin C. Rinard

Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, 2019

2018

Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data.

José Pablo Cambronero, Phillip Stanley-Marbell, Martin C. Rinard

CoRR, 2018

2017

Query Optimization for Dynamic Imputation.

José Cambronero, John K. Feser, Micah J. Smith, Samuel Madden

Proc. VLDB Endow., 2017