A Symmetric Layer-Union Audit of Component Collapse in Hierarchical Procedural Corpora
Jiuyi Zheng, Gan Xu
Abstract
Component-disjoint leakage control can group corpus units by content similarity, hierarchical membership, or both. Guvenilir and Dogan previously showed that merging relation types can create a giant component that obstructs splitting; we do not claim this phenomenon as new. We examine it through a symmetric audit of a content-near-duplicate layer, a common-container layer, and their union in a fixed panel of six hierarchical procedural corpora. MyFixit and Doc2Dial exhibit the individual-layer-pass/union-fail pattern under the same operational criteria. The resulting two-of-six fraction describes this deliberately constructed panel and is not a prevalence estimate. A prespecified bridge-specific predictor is associated with the pattern, but it is not distinguished from a registered union-density control; the panel therefore does not identify a bridge-specific mechanism. Secondary diagnostics bound the interpretation of threshold sensitivity, annotation coverage, and lexical cues without extending those findings beyond their recorded sources and definitions. The paper's contribution is a bounded measurement and audit: it keeps relation families visible, evaluates their individual and union component structures symmetrically, and reports negative cases and mechanism limits. It proposes neither a new splitting algorithm nor a general causal claim about relation unions.
Create a lesson
Related papers
SURF: Subtractive Updates for Recommender Forgetting
Filippo Betello, Antonio Purificato, Nicola Tonellotto et al.
Exploring LLMs and RAG for Plausible and Explainable Material Prediction of Vehicle Components
Frederik Wagner, Annerose Eichel, Sabine Schulte im Walde
One-Step Retrieval Framework for Real-Time Sponsored Search Ads Using Hierarchical Text Representations
Tongtong Liu, Renyu Zhang, Jiayu Ding et al.
Quanta: A Self-Contained Python Library for Hybrid Retrieval over Quantised Embeddings, Lexical Indexes, and Knowledge Graphs
Ioannis E. Livieris
Single-Token Expected-Value Scoring for Cold-Start Candidate Ranking
Qihang Wang, Jinwei Tan, Mengyuan Shi et al.
PageRecall: Measuring Page Selection in Literature-Grounded Question Answering
Aaditya Chauhan