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New Semantic Contract USP Standardizes Information Extraction Tasks

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced USP, a novel semantic contract designed to standardize information extraction and intent-slot parsing across various datasets. This contract provides a unified interface for tasks like named-entity recognition and relation extraction, along with five diagnostic views to assess different aspects of system performance. A fine-tuned Xing4.0-29B-Intent model demonstrated superior performance, achieving a 57.70 task-balanced Field-Value Micro-F1 score and outperforming other models significantly, particularly in complete-instance recovery. AI

IMPACT Standardizes evaluation for information extraction tasks, enabling more accurate comparisons between models.

RANK_REASON The cluster describes a new academic paper introducing a novel framework and evaluation protocol for information extraction tasks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Semantic Contract USP Standardizes Information Extraction Tasks

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The cluster describes a new academic paper introducing a novel framework and evaluation protocol for information extraction tasks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhongqiu Li, Boyang Wang, Ruiyu Fang, Shiquan Wang, Di Wu, Jiayi Liang, Feilong Zhang, Hongfeng Du, Xiaomeng Huang, Mengjiao Bao, Luwen Pu, Xuewei He, Yu Zhao, Chao Wang, Kaidong Yu, Bingkai Yang, Qingjun Zhu, Shaoyi Du, Shuangyong Song, Yongxiang Li ·

    Xing USP: A Cross-Family Semantic Contract for Information Extraction and Intent-Slot Parsing

    arXiv:2610.34343v1 Announce Type: cross Abstract: Structured semantic parsing is typically judged by whether the correct category is assigned, which leaves value recovery and instance-level associations unexamined: a system may recognize an event yet bind an argument to the wrong…

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