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New semantic contract USP enhances structured parsing evaluation

Researchers have introduced USP, a novel cross-family semantic contract designed to improve structured semantic parsing by evaluating not just category assignment but also value recovery and instance associations. This contract, paired with five diagnostic matching views, normalizes 61 datasets into a unified corpus. A fine-tuned Xing4.0-29B-Intent model achieved a 57.70 task-balanced Field-Value Micro-F1 score, outperforming other models significantly, especially in complete-instance recovery, highlighting the limitations of traditional category-based evaluations. AI

IMPACT This new evaluation framework and model performance could lead to more robust and accurate information extraction systems in AI applications.

RANK_REASON The cluster describes a new research paper introducing a novel semantic contract and evaluation protocol for information extraction and intent-slot parsing.

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New semantic contract USP enhances structured parsing evaluation

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The cluster describes a new research paper introducing a novel semantic contract and evaluation protocol for information extraction and intent-slot parsing.
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COVERAGE [2]

  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…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

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

    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 instance, or identify an intent yet supply an inc…