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cs.LG2026
Learning Lookahead Lemmas for Neural Network Verification
Liam Davis, Haoze Wu
State-of-the-art neural network verifiers use the branch-and-bound procedure as their core solving mechanism. We introduce an inprocessing framework for neural network verification…
cs.LG2026
Lookahead Branching for Neural Network Verification
Liam Davis, Duo Zhou, Huan Zhang +3
In this work, we investigate the effect of lookahead branching strategies in neural network verification. We present a general recipe to integrate lookahead into any branch-and-bou…
cs.DB2026
SpotIt+: Verification-based Text-to-SQL Evaluation with Database Constraints
Andrew Tremante, Yang He, Rocky Klopfenstein +3
We present SpotIt+, an open-source tool for evaluating Text-to-SQL systems via bounded equivalence verification. Given a generated SQL query and the ground truth, SpotIt+ actively…