Derives an information-theoretic accuracy upper bound for single-pass LLM multi-hop QA and introduces the InfoQA multi-call framework that improves performance by keeping per-step information load within model capacity.
Why johnny can’t prompt: how non-ai experts try (and fail) to design llm prompts
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A Fano-Style Accuracy Upper Bound for LLM Single-Pass Reasoning in Multi-Hop QA
Derives an information-theoretic accuracy upper bound for single-pass LLM multi-hop QA and introduces the InfoQA multi-call framework that improves performance by keeping per-step information load within model capacity.