Papers with BIO tagging

2 papers
IDP Accelerator: Agentic Document Intelligence from Extraction to Compliance Validation (2026.acl-demo)

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Challenge: Large Language Models (LLMs) are inadequate for extracting structured insights from unstructured documents.
Approach: They propose a framework enabling agentic AI for end-to-end document intelligence with four key components: DocSplit, configurable Extraction Module, and Rule Validation Module.
Outcome: The proposed framework achieves 98% classification accuracy, 80% reduced processing latency, and 77% lower operational costs over legacy baselines.
Linguistically Motivated Sign Language Segmentation (2023.findings-emnlp)

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Challenge: Sign language segmentation is a crucial task in sign language processing systems.
Approach: They propose to combine two kinds of segmentation: segmentation into individual signs and segmentation to segment into phrases, larger units comprising several signs.
Outcome: The proposed model is based on linguistic cues observed in sign language corpora and replaces the predominant IO tagging scheme with BIO taging to account for continuous signing.

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