Apple's SSR framework cuts multimodal search agent reasoning latency by over 90%
Original titleSelection-Based Structured Reasoning: Toward Efficient Multimodal Search Agents
AISummary
Apple researchers introduce Selection-based Structured Reasoning (SSR), which has multimodal search agents select from pre-specified reasoning candidates instead of generating freeform reasoning.
SSR reduces per-turn reasoning latency by over 90% and total per-question inference latency by 28–54% on 2B and 4B models.
The authors say its average success rate is competitive with leading search agents of the same scale across seven multimodal search benchmarks.
Source: Apple Machine Learning Research · machinelearning.apple.comPublished · added here