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IterSynth separates search planning from synthesis and scores 50.7 on deep-search benchmarks

huggingface.co Editor score 8/10

IterSynth alternates a planner with a synthesizer that maintains a summary state, and the paper reports an average score of 50.7 for IterSynth-8B across five long-horizon benchmarks. The design addresses context growth and role coupling in deep-search agents.

What

IterSynth separates deep-search planning and synthesis, using a Planner and Synthesizer with an evolving summary as persistent search state.

Method

The Planner identifies information needs; the Synthesizer integrates evidence into the summary; RDPO uses outcome rewards and turn-level rubric scores for role-specific credit assignment.

Why it matters

Separating roles and summarizing search history aims to reduce context noise in long-horizon agent tasks.

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