Cascaded Batch Prompting

Abstract:Although batch prompting makes large language model inference more efficient by processing multiple instances simultaneously, it suffers from unpredictable downstream task performance. We propose cascaded batch prompting, a two-stage approach designed to resolve the unpredictability of conventional batch prompting by disentangling complex reasoning from symbol grounding. Experiments on multiple-choice question answering and natural language inference demonstrate that the proposed method outperforms the standard single prompting baseline while achieving a speedup proportional to batch size, establishing a new state of the art on the Pareto frontier.

Computation and Language (cs.CL)

arXiv:2608.27038 [cs.CL]

(or arXiv:2608.27038v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.27038 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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