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cs.LG2026
Fork-and-Flush: Escaping Idea Basins in Autoresearch Agents
Ziyang Cai, Christos Ziakas, Vasilis Kontonis +5
Autoresearch agents tackle open-ended problems by repeatedly proposing candidate solutions, evaluating them, and using feedback to guide subsequent experiments. We show that indepe…
cs.LG2026
JumpStart Your Policy Learning with Lessons from 160,000 Training Runs
Nabil Omi, Eric Bae, Chung Yik Edward Yeung +2
Reliable progress in offline policy learning depends on careful reporting, well-tuned baselines, and evaluation across diverse conditions. Prior work has shown that results can be…
cs.CL2026
Hierarchical Latent Prediction for Language Models
Chang Shi, Tim Pearce, Manan Tomar +2
While standard Next-Token Prediction (NTP) lays the foundation of language model pre- training, its teacher-forced training paradigm may not be optimal for long-horizon reasoning a…