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Found 4 papers, 1 papers with code
Can GPT-4 Replicate Empirical Software Engineering Research?
We specifically study their ability to surface assumptions made in empirical software engineering research methodologies, as well as their ability to plan and generate code for analysis pipelines on seven empirical software engineering papers.
LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs
We reflect on human and LLMs' different sensitivities to instructions, stress the importance of enabling human-facing safeguards for LLMs, and discuss the potential of training humans and LLMs with complementary skill sets.
NLPositionality: Characterizing Design Biases of Datasets and Models
We introduce NLPositionality, a framework for characterizing design biases and quantifying the positionality of NLP datasets and models.
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
We also found the most important reasons why developers do not use these tools are because these tools do not output code that addresses certain functional or non-functional requirements and because developers have trouble controlling the tool to generate the desired output.
