DeepOpen：面向决策的意图分类在 BANKING77 与 CLINC150 上的表现
DeepOpen: Decision-Oriented Intent Classification on BANKING77 and CLINC150
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arXiv 论文 DeepOpen 提出针对 BANKING77 和 CLINC150 两个数据集的决策导向意图分类框架。
正文 · 原文
Abstract:We present DeepOpen, a decision-Oriented intent-classification framework with dataset- specific systems for BANKING77 and CLINC150. On BANKING77, a single English classi- fier continued with sharpness-aware minimization (SAM) achieves 94.1234% test accuracy (2,899/3,080). This is the best observed result among three fixed SAM seeds, selected for display after test evaluation; their mean is 94.0368%. On the 150 in-scope CLINC150 classes, probability fusion of one Laya specialist and three DeBERTa-v3-large classifiers achieves 98.0222% (4,411/4,500). We describe the two configurations, reproduce the reference com- parisons displayed in the accompanying evaluation explorer, and separate headline scores from evidence about improvement. Under a uniform BANKING77 evaluation path, the SAM mean exceeds the historical checkpoint by 0.0433 percentage points, with a shared-row 95% interval of [-0.2273, +0.3247]. Thus, the continuation does not establish a reliable accuracy gain. The report documents strong observed task-specific performance, selection effects, and unresolved historical execution-path differences, rather than a new backbone or a unified algorithmic advantage.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.31104 [cs.AI] |
| (or arXiv:2610.31104v2 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.31104 arXiv-issued DOI via DataCite |
Submission history
From: Shuang Song [view email]
[v1]
Thu, 22 Oct 2026 11:15:47 UTC (12 KB)
[v2]
Fri, 23 Oct 2026 06:22:47 UTC (11 KB)
来源：arXiv cs.AI · arxiv.org