ScaffoldAgent: Utility-Guided Dynamic Outline Optimization for Open-Ended Deep Research

arXiv:2606.20122 · cs.AI, cs.MA · Submitted 2026-06-18 · Read on arXiv

cs.AI, cs.MA

Submitted: 2026-06-18

Updated: 2026-08-30

Comments: 9 pages, 6 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Grounding — 13× in this paper · explained in 3 episodes
• Open-ended Deep Research — 13× in this paper
• Redundancy — 13× in this paper · explained in 2 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• LLM judge — 11× in this paper · explained in 2 episodes
• RAG — 7× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Adam — 4× in this paper · explained in 2 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Cosine Similarity — 4× in this paper · explained in 3 episodes
• Semantic Similarity — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Enterprise Deep Research — 2× in this paper
• Iterative Refinement — 2× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Agentic Reasoning — 1× in this paper · explained in 1 episode
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Information Gain — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Local Optimization — 1× in this paper · explained in 2 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Paper Review — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Test-time Scaling — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Research
• DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents
• Deep Researcher with Test-Time Diffusion
• OpenAI o1 System Card
• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
• RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
• AgentCPM-Report: Interleaving Drafting and Deepening for Open-Ended Deep Research
• WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research
• DeepSeek-V3 Technical Report
• Teaching language models to support answers with verified quotes
• Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• SciSage: A Multi-Agent Framework for High-Quality Scientific Survey Generation
• WebShaper: Agentically Data Synthesizing via Information-Seeking Formalization
• Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
• SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models
• Qwen3 Technical Report
• ReAct: Synergizing Reasoning and Acting in Language Models
• StackPlanner: A Centralized Hierarchical Multi-Agent System with Task-Experience Memory Management

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