More Than Can Be Said: A Benchmark and Framework for Pre-Question Scientific Ideation

Researchers introduce InciteResearch, a multi-agent AI framework that helps researchers transform vague, implicit research ideas into structured, actionable questions through Socratic questioning. The framework achieves significant improvements over baselines on TF-Bench, a new benchmark for tacit-to-explicit research assistance, demonstrating AI's potential as a thinking tool rather than just an execution automator.

InciteResearch addresses a fundamental gap in AI research assistance: most tools assume researchers already have clearly defined questions, but human discovery often begins with nebulous friction points and unformed intuitions. This framework reframes the research ideation process by decomposing Socratic questioning into a systematic pipeline that converts implicit understanding into explicit, inspectable reasoning. The approach decomposes research conceptualization into three stages—profiling researcher context through friction points, challenging hidden assumptions via feasibility-novelty optimization with causal tracing, and validating necessity of proposed methods.

The introduction of TF-Bench marks the first systematic effort to benchmark research ideation quality, distinguishing between domain-related and domain-unrelated inspirations across scientific modes. InciteResearch's performance gains—shifting from recombination-based proposals (3.671 novelty) to architectural insights (4.250 novelty)—suggest meaningful qualitative improvements in research question generation. This work reflects broader trends in AI moving beyond task automation toward augmenting human cognition itself.

For the research and AI community, this development signals growing maturity in AI-assisted discovery pipelines. Rather than replacing researcher judgment, the framework extends human thinking capacity at critical early stages where most impact occurs. The structured methodology could accelerate research timelines across domains, particularly benefiting early-career researchers or those exploring interdisciplinary spaces.

Future attention should focus on whether these gains generalize across diverse scientific domains and how researchers actually adopt such tools in practice. The tension between automated ideation and researcher autonomy remains crucial for meaningful human-AI collaboration.

• →InciteResearch converts vague research friction into structured questions through distributed Socratic questioning across a multi-agent pipeline.
• →TF-Bench provides the first benchmark specifically designed for evaluating tacit-to-explicit research assistance quality.
• →The framework achieves 15-17% improvements in novelty and impact metrics compared to prompt-based baselines.
• →AI research ideation tools demonstrate potential to augment human thinking at early discovery stages rather than automating downstream tasks.
• →Successful research question generation requires explicit modeling of researcher context, assumption violation, and methodological necessity.