Author

Amirhossein Abaskohi

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#natural language process... Preprint Oct 2026

SEDIMA: Cross-Run Hierarchical Insight Memory for Evolutionary Search Agents

Large language model (LLM)-driven evolutionary search is a powerful paradigm for automated program and algorithm discovery, yet existing systems are largely memoryless: each run explores from scratch, so agents repeatedly rediscover the same improvements and re-encounter the same dead ends. We introduce SEDIMA, a persi...

Amirhossein Abaskohi, Mahdi Mostajabdaveh, Zi-Rui Zhou · 0 citations

#natural language process... Preprint Sep 2026

DeepRewind: Predicting and Repairing Premature Commitments in Deep Research Agents

Deep-research agents conduct long-horizon investigations through iterative search, evidence evaluation, belief revision, and synthesis. However, they may commit to claims before sufficient evidence is available, causing later reasoning to reinforce an incorrect interpretation. We introduce DeepRewind, an additive contr...

Amirhossein Abaskohi, Amirhossein Dabiriaghdam, Le-Le Wang et al. · 0 citations