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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Bibliographische Detailangaben

Veröffentlicht in:	Proceedings of ACM on programming languages Jg. 9; H. OOPSLA2; S. 1455 - 1483
Hauptverfasser:	Barnaby, Celeste, Chen, Qiaochu, Ramalingam, Ramya, Bastani, Osbert, Dillig, Işıl
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY, USA ACM 09.10.2025
Schlagworte:	Automatic programming Software and its engineering Neurosymbolic Synthesis Conformal Prediction Active Learning Program Synthesis
ISSN:	2475-1421, 2475-1421
Online-Zugang:	Volltext
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