Beyond Parallel Sampling: Diverse Query Initialization for Agentic Search
📰 ArXiv cs.AI
Learn how to improve agentic search with diverse query initialization, moving beyond parallel sampling for better results
Action Steps
- Apply diverse query initialization to agentic search models to reduce query redundancy
- Configure models to issue distinct first queries across rollouts
- Test the impact of diverse query initialization on retrieval overlap and subsequent turns
- Compare the performance of standard parallel sampling with diverse query initialization
- Run experiments to evaluate the effectiveness of breadth scaling with diverse query initialization
Who Needs to Know This
Researchers and engineers working on agentic search and AI systems can benefit from this knowledge to improve their models' performance and efficiency
Key Insight
💡 Diverse query initialization can help reduce query redundancy and improve the efficiency of agentic search models
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🚀 Improve agentic search with diverse query initialization! 🤖
Full Article
Title: Beyond Parallel Sampling: Diverse Query Initialization for Agentic Search
Abstract:
arXiv:2606.17209v1 Announce Type: new Abstract: Test-time scaling for agentic search typically increases depth (i.e., more turns and tokens per trajectory) or breadth (i.e., more parallel rollouts). Here we focus on breadth scaling, showing that standard parallel sampling yields diminishing returns, tracing this to query redundancy at the first turn. When models issue similar first queries across rollouts, the threads retrieve overlapping evidence, and subsequent turns are conditioned on this sh
Abstract:
arXiv:2606.17209v1 Announce Type: new Abstract: Test-time scaling for agentic search typically increases depth (i.e., more turns and tokens per trajectory) or breadth (i.e., more parallel rollouts). Here we focus on breadth scaling, showing that standard parallel sampling yields diminishing returns, tracing this to query redundancy at the first turn. When models issue similar first queries across rollouts, the threads retrieve overlapping evidence, and subsequent turns are conditioned on this sh
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