An Interactive Agent for Requirement-Driven Candidate Sourcing

📅 2026-08-24
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🤖 AI Summary
本文提出一种基于需求工程的交互式候选人筛选代理系统,通过明确、验证和确认需求来提高从自然语言描述中寻找合适人选的准确性。
📝 Abstract
Finding people from a natural-language description (``ML engineers transitioning to research roles in biotech'') is increasingly delegated to LLM agents and framed as information retrieval. We argue that it is fundamentally a requirements engineering task: such a request is an under-determined requirement with implicit constraints, many valid answers, and no acceptance criterion, so useful answers require eliciting, validating, and verifying the requirement before search can matter. We present \sys{}, to our knowledge the first interactive, requirements-driven candidate-sourcing agent (it elicits, validates, retrieves, and verifies a vague people-request into a justified slate through bounded elicitation, workflow templates, a two-stage commit protocol, and bidirectional termination guards) and \bench{}, a benchmark that runs the requirements lifecycle (criteria-anchored validation, multi-model evidence-grounded oracle construction, and cost-aware verification). Across $21$ systems and all $691$ requirements, \sys{} dominates breadth ($100%$ coverage at $2.5\times$ the yield) and is \emph{near-orthogonal} to the field, with $90%$ of the people it returns are surfaced by \emph{none} of $20$ strong LLM-plus-web baselines combined. Beyond breadth, an evidence-grounded judging of every system shows \sys{} \emph{recalls} the most relevant real people: $0.241$ of the union pool, $1.9\times$ the next system, with a bootstrap $95%$ interval disjoint from every baseline. \sys{} is thus the strongest \emph{sourcing} engine (the deepest real, reachable candidate pool), while precision-ranking LLMs serve as~complementary verifiers.
Problem

Research questions and friction points this paper is trying to address.

requirement engineering
candidate sourcing
natural language description
information retrieval
implicit constraints
Innovation

Methods, ideas, or system contributions that make the work stand out.

interactive agent
requirement-driven candidate sourcing
bounded elicitation
two-stage commit protocol
bidirectional termination guards
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