Using partial label learning losses, especially Libra and meritocratic losses, improves the plCoP theorem prover's solved-problem count by roughly 14 to 28 percent over the MCTS-imitation baseline.
Lucas, Peter I
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Partial Label Learning for Automated Theorem Proving
Using partial label learning losses, especially Libra and meritocratic losses, improves the plCoP theorem prover's solved-problem count by roughly 14 to 28 percent over the MCTS-imitation baseline.