Cascaded Batch Prompting
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Computer Science > Computation and Language
Title: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.
| Comments: | EMNLP 2026 Findings |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2608.27038 [cs.CL] |
| (or arXiv:2608.27038v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.27038
arXiv-issued DOI via DataCite (pending registration)
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