arXiv cs.AI· Nathaniel Chen, Kouroche Bouchiat, Peter Steiner, Andrew Rothstein, David Smith, Max Austin, Mike van Zeeland, Marie Roch, Azarakhsh Jalalvand, Egemen Kolemen·· 5 小时前AI 评分41
TokEye：跨时频测量的相干模式通用提取方法
A general extractor for coherent patterns across time-frequency measurements
AI 导读
TokEye 是一种无需参考标注的通用方法，从异构融合测量数据中学习相干结构的判别准则，无需重训练即可跨领域提取信号。该方法恢复 82.5% 的专家标注仿星器信号，检测 78% 的海豚哨声，在六个基准上以 81.5% 平均精度识别雷达事件，GPU 上处理完整实验频谱图不到一秒。
正文 · 原文
Abstract:Scientific discovery increasingly depends on finding meaningful patterns within volumes of sensor data too large for manual inspection. Existing time-frequency event extractors are often engineered or trained on manually labeled examples for each instrument, which can be laborious and difficult to adapt to new environments. To address this, we introduce TokEye, a reference-free method that learns a general criterion for coherent structure from heterogeneous fusion measurements. A model developed under this method, without retraining, can extract signals from various other fields including marine bioacoustics and wideband radar. It recovers 82.5\% of expert-annotated stellarator signals, detects 78\% of dolphin whistles, and identifies radar events with 81.5\% average precision across six benchmarks, while processing full experimental spectrograms in under one second on a GPU. This transfer across unrelated sensors and physical systems reveals common exploitable structure in time-frequency measurements and establishes a scalable foundation for automated scientific signal discovery.
| Subjects: | Signal Processing (eess.SP); Artificial Intelligence (cs.AI); Plasma Physics (physics.plasm-ph) |
| Cite as: | arXiv:2602.20317 [eess.SP] |
| (or arXiv:2602.20317v3 [eess.SP] for this version) | |
| https://doi.org/10.48550/arXiv.2602.20317 arXiv-issued DOI via DataCite |
Submission history
From: Nathaniel Chen [view email]
[v1]
Mon, 23 Feb 2026 20:03:10 UTC (8,811 KB)
[v2]
Thu, 26 Feb 2026 01:13:38 UTC (8,811 KB)
[v3]
Tue, 27 Oct 2026 22:14:47 UTC (30,925 KB)
来源：arXiv cs.AI · arxiv.org