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cs.AI2026
Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards
Tianyu Liu, Davide Belli, Bence Major +2
Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification, both expensive to construct f…
cs.MA2026
When Cloud Agents Meet Device Agents: Lessons from Hybrid Multi-Agent Systems
Corrado Rainone, Davide Belli, Bence Major +1
The design space of agentic AI inference spans two extremes: frontier large language models (LLMs), typically hosted in the cloud and offering strong performance across a wide rang…