Asking for What Was Never Requested: horizontal and vertical proactivity in LLM agents. Need-graph metrics (no LLM judge) and Q&D, which trains a questioner from the consequences of its questions.
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Updated
Oct 4, 2026 - Python
Asking for What Was Never Requested: horizontal and vertical proactivity in LLM agents. Need-graph metrics (no LLM judge) and Q&D, which trains a questioner from the consequences of its questions.
AskBench: LLM question-asking/clarification benchmark & dataset with evaluation and training code (paper: arXiv 2602.11199).
Code for data processing, analysis, and visualization for a project exploring the development of question-asking in natural conversation
Today's AI answers. This one asks. An RL environment where an agent learns to understand any subject by asking the sharpest questions — collapsing a field of candidates to the truth in as few questions as possible.
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