3 papers
cs.AI2026
Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluation
Julia Belikova, Rauf Parchiev, Evgeny Egorov +4
Procedural memory is increasingly used to improve LLM agents on recurring workplace tasks, yet its ability to produce reusable skills remains poorly understood. We introduce AFTER,…
cs.LG2026
TreeDQN: Sample-Efficient Off-Policy Reinforcement Learning for Combinatorial Optimization
D. Sorokin, A. Kostin, L. Savchenko +2
A convenient approach to optimally solving combinatorial optimization tasks is the Branch-and-Bound method. Its branching heuristic can be learned to solve a large set of similar t…
cs.LG2026
Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
Artem Sakhno, Ivan Sergeev, Alexey Shestov +5
Industrial financial systems operate on temporal event sequences such as transactions, user actions, and system logs. While recent research emphasizes representation learning and l…