Alex Gu

According to our database1, Alex Gu authored at least 19 papers between 2021 and 2024.

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Bibliography

2024
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.
Trans. Mach. Learn. Res., 2024

Mixture of Parrots: Experts improve memorization more than reasoning.
CoRR, 2024

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.
CoRR, 2024

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.
CoRR, 2024

StarCoder 2 and The Stack v2: The Next Generation.
CoRR, 2024

Language Agnostic Code Embeddings.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
StarCoder: may the source be with you!
Trans. Mach. Learn. Res., 2023

Certified Interpretability Robustness for Class Activation Mapping.
CoRR, 2023

SantaCoder: don't reach for the stars!
CoRR, 2023

LeanDojo: Theorem Proving with Retrieval-Augmented Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
ObSynth: An Interactive Synthesis System for Generating Object Models from Natural Language Specifications.
CoRR, 2022

Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning.
CoRR, 2022

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.
CoRR, 2022

2021
Reproducibility Report: La-MAML: Look-ahead Meta Learning for Continual Learning.
CoRR, 2021

Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


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