Batch-of-Thought enables cross-instance learning by jointly processing related queries in batches, yielding higher accuracy and up to 61% lower inference costs on LLM reasoning tasks.
These methods are ef- ficient but highly sensitive to prompt formatting (Si et al., 2024) and often produce overconfident pre- dictions (Kadavath et al., 2022)
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Batch-of-Thought: Cross-Instance Learning for Enhanced LLM Reasoning
Batch-of-Thought enables cross-instance learning by jointly processing related queries in batches, yielding higher accuracy and up to 61% lower inference costs on LLM reasoning tasks.