The Communication Bottleneck: A Round-Trip Study of Tree-Structured

Communication Bottleneck: what actually changed

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Communication Bottleneck: how it works

8. Drafting Section 5: ## Communication Bottleneck: what to watch Constraint Check: Exactly two paragraphs, each 80-160 words. No bold/bullets. Focus: What to watch (what builders should verify, future application of this evaluation protocol, model testing). Drafting Paragraph

Communication Bottleneck: why it matters now

We propose a round-trip protocol that answers this question empirically for tree-structured expressions. A generator converts a procedurally generated arithmetic expression into a word problem, a separate extractor recovers the expression from the word problem alone, and symbolic equivalence provides an exact oracle.

Communication Bottleneck: who is affected

Evaluating all pairwise combinations of sixteen models yields a communication matrix whose marginals separate generation quality from extraction quality. First, the channel is lossy and asymmetric: swapping which model generates and which extracts shifts accuracy by up to 60.4 points, and the best pair reaches 92.9% by combining different models on each end rather than the same model on both.

Communication Bottleneck: what to watch

Second, at least 73.6% of round-trip failures originate at generation, and difficulty is driven by tree structure (operator count, depth, right-branching) rather than model family. See the full write-up from Apple Machine Learning Research via the source link for quotes and complete context.