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Active Learning for Neurosymbolic Program Synthesis
Celeste Barnaby, Qiaochu Chen, Ramya Ramalingam +2
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 ac…
cs.PL2025
Automated Discovery of Tactic Libraries for Interactive Theorem Proving
Yutong Xin, Jimmy Xin, Gabriel Poesia +3
Enabling more concise and modular proofs is essential for advancing formal reasoning using interactive theorem provers (ITPs). Since many ITPs, such as Rocq and Lean, use tactic-st…