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cs.AI2026
Open-world AI: a Tale of Three Requirements
Jianyu Zhang, Léon Bottou
The closed world asks AI for specialized competence and lets it manufacture the iid data its theory assumes: a fixed criterion licenses collecting examples until the task is covere…
cs.AI2026
LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent
Bince Qu, Wanli Li, Bo Pan +5
Reinforcement Learning (RL) has emerged as a powerful training paradigm for LLM-based agents. However, scaling agentic RL for deep research remains constrained by two coupled chall…
cs.AI2025
Memory Mosaics at scale
Jianyu Zhang, Léon Bottou
Memory Mosaics [Zhang et al., 2025], networks of associative memories, have demonstrated appealing compositional and in-context learning capabilities on medium-scale networks (GPT-…