most citedUniversal Self-Consistency for Large Language Model Generation

10 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2024★ 8 cited

Natural Language Outlines for Code: Literate Programming in the LLM Era

Kensen Shi, Deniz Altınbüken, Saswat Anand +17

We propose using natural language outlines as a novel modality and interaction surface for providing AI assistance to developers throughout the software development process. An NL…

cs.DB2024★ 2 cited

UQE: A Query Engine for Unstructured Databases

Hanjun Dai, Bethany Yixin Wang, Xingchen Wan +7

Analytics on structured data is a mature field with many successful methods. However, most real world data exists in unstructured form, such as images and conversations. We investi…

cs.LG2024★ 6 cited

NExT: Teaching Large Language Models to Reason about Code Execution

Ansong Ni, Miltiadis Allamanis, Arman Cohan +4

A fundamental skill among human developers is the ability to understand and reason about program execution. As an example, a programmer can mentally simulate code execution in natu…

cs.CL2024

Naive Bayes-based Context Extension for Large Language Models

Jianlin Su, Murtadha Ahmed, Wenbo +3

Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations…

cs.CL2023★ 10 cited

Universal Self-Consistency for Large Language Model Generation

Xinyun Chen, Renat Aksitov, Uri Alon +7

Self-consistency with chain-of-thought prompting (CoT) has demonstrated remarkable performance gains on various challenging tasks, by utilizing multiple reasoning paths sampled fro…