16 citations · 16 across the 1 of their papers we have counts for
3 papers · 1 filter
Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning
Kavi Gupta, Kate Sanders, Armando Solar-Lezama
While LLMs have revolutionized the field of machine learning due to their high performance on a strikingly wide range of problems, they are also known to hallucinate false answers…
Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
Kavi Gupta, Peter Ebert Christensen, Xinyun Chen +1
The use of deep learning techniques has achieved significant progress for program synthesis from input-output examples. However, when the program semantics become more complex, it…
Synthetic Datasets for Neural Program Synthesis
Richard Shin, Neel Kant, Kavi Gupta +4
The goal of program synthesis is to automatically generate programs in a particular language from corresponding specifications, e.g. input-output behavior. Many current approaches…