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School of Integrated Circuits, Southeast University
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Unlocking the potential of compute-in-memory accelerators for LLMs requires carefully navigating a complex dataflow design space, and AccelCIM provides the first systematic framework to do so.
Multi-agent systems for automated research face a fundamental trade-off: parallel exploration offers speed and stability, while expert teams unlock deeper reasoning at the cost of increased fragility.
