AgentStream: How Well Do Self-Evolving LLM Agents Perform Under Streaming Tasks?

arXiv cs.AIAugust 4, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2608.00155v1 Announce Type: new Abstract: Large language model (LLM) agents can self-evolve by continually improving from their own accumulated experience. However, existing studies predominantly adopt independent evaluation. Consequently, the behavior of self-evolving agents in realistic streaming settings, where agents adapt to diverse and complex task streams, remains poorly understood. To address this gap, we introduce AgentStream, a unified framework that evaluates self-evolving agents spanning diverse evolution components by organizing agentic benchmarks into a configurable task stream and instantiating the \texttt{Isolated}, \texttt{Sequential}, and \texttt{Interleaved} streamin

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