mlsanityData to 7 Oct 2026

Lookahead Branching for Neural Network Verification

arXiv 2607.17290 ↗First posted 19 Jul 2026cs.LG cs.AI cs.LOcited by 1

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Abstract (arXiv)

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-bound verifier and demonstrate how one of the current state-of-the-art branching heuristics, FSB, can be viewed as a special instantiation of the lookahead branching strategy. We also describe how, in addition to improving the quality of branching decisions, lookahead can generate additional lemmas that accelerate verification. We instantiate the method in two representative branch-and-bound-based verifiers (Marabou and α-β-CROWN), and demonstrate that lookahead leads to consistent speedups in verification time and up to 57% more solved instances. Code is available at https://github.com/ai-ar-research/lookahead-branching.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 15 of its 24 references that are in the map. First posted on arXiv 19 Jul 2026.

Builds on

15 of 24 references.

References · 15

  1. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,590
  2. 2017Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networkscited by 739
  3. 2018Efficient Neural Network Robustness Certification with General Activation Functionscited by 439
  4. 2024Reinforcement learningcited by 236
  5. 2017Deep Reinforcement Learning framework for Autonomous Drivingcited by 224
  6. 2020Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifierscited by 183
  7. 2019Branch and Bound for Piecewise Linear Neural Network Verificationcited by 138
  8. 2022General Cutting Planes for Bound-Propagation-Based Neural Network Verificationcited by 102
  9. 2024Marabou 2.0: A Versatile Formal Analyzer of Neural Networkscited by 81
  10. 2024Neural Network Verification with Branch-and-Bound for General Nonlinearitiescited by 47
  11. 2019Neural Network Branching for Neural Network Verificationcited by 45
  12. 2020Parallelization Techniques for Verifying Neural Networkscited by 36
3 more
  1. 2024Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planescited by 33
  2. 2022Efficient Neural Network Analysis with Sum-of-Infeasibilitiescited by 24
  3. 2025Clip-and-Verify: Linear Constraint-Driven Domain Clipping for Accelerating Neural Network Verificationcited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Learning Lookahead Lemmas for Neural Network Verificationcited by 0