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New active learning method enhances table extraction pipelines

By PulseAugur Editorial · [2 sources] ·

Researchers have adapted an active learning strategy called Uncertainty Herding (UHerding) for cascaded object detection pipelines used in table extraction. This adaptation aims to reduce the costly annotation burden, particularly for Table Structure Recognition (TSR). The proposed extensions, RankFusion and CAPA, leverage the dependency between Table Detection (TD) and TSR stages by incorporating dual-manifold coverage and stage-dependent gating with uncertainty calibration. Experiments on multiple datasets demonstrate that UHerding outperforms baseline methods, with CAPA emerging as a consistent and effective strategy. AI

IMPACT This research could lead to more efficient and cost-effective training of AI models for document analysis and data extraction.

RANK_REASON The cluster contains an academic paper detailing a new method for machine learning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New active learning method enhances table extraction pipelines

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Eliott Thomas, Mickael Coustaty, Aurelie Joseph, Gaspar Deloin, Vincent Poulain d'Andecy, Jean-Marc Ogier ·

    Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines

    arXiv:2607.00747v1 Announce Type: cross Abstract: Table extraction from business documents relies on a cascaded pipeline where Table Detection (TD) first localizes tables and Table Structure Recognition (TSR) then recovers their internal layout. Building task-specific training se…

  2. arXiv cs.AI TIER_1 English(EN) · Jean-Marc Ogier ·

    Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines

    Table extraction from business documents relies on a cascaded pipeline where Table Detection (TD) first localizes tables and Table Structure Recognition (TSR) then recovers their internal layout. Building task-specific training sets for this pipeline is costly, particularly for T…

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