Active Learning for Neurosymbolic Program Synthesis

The goal of active learning for program synthesis is to synthesize the desired program by asking targeted questions that minimize user interaction. While prior work has explored active learning in the purely symbolic setting, such techniques are inadequate for the increasingly popular paradigm of ne...

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Vydané v:	Proceedings of ACM on programming languages Ročník 9; číslo OOPSLA2; s. 1455 - 1483
Hlavní autori:	Barnaby, Celeste, Chen, Qiaochu, Ramalingam, Ramya, Bastani, Osbert, Dillig, Işıl
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY, USA ACM 09.10.2025
Predmet:	Automatic programming Software and its engineering Neurosymbolic Synthesis Conformal Prediction Active Learning Program Synthesis
ISSN:	2475-1421, 2475-1421
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