AI RESEARCH
CL-bench Life: Can Language Models Learn from Real-Life Context?
arXiv CS.CL
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ArXi:2604.27043v1 Announce Type: new Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for models. As these systems move beyond professional settings into everyday life, the nature of the contexts they must handle also shifts. Real-life contexts are often messy, fragmented, and deeply tied to personal and social experience, such as multi-party conversations, personal archives, and behavioral traces.