Have an LLM Write Your Anomaly Detector: Autonomous Discovery of Compact, Interpretable Detectors for Time Series

An LLM autonomously searches for short NumPy anomaly detectors that lead the TSB-AD benchmark using spectral features and covariance-aware distances without neural networks or GPUs.

David Berghaus

Published Oct 1, 2026 · 0 citations

Online Change-point Detection using Foundation Probabilistic Forecasting Models

Alan Moore, Zhengyuan Zhu, Lynna Chu

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

Layer Precision Reduction for Deep Anomaly Detection

jiawei Yang, Xu Tan, Matti Kaisti

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Supervision Recovery for Time Series Anomaly Detection via Counterfactual Pairing

Yifei Gao, Tian Lan, Yimeng Lu, Xuming An and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Combating Camouflage and Forgetting: Spatio-Temporal Dual Denoising for Money Laundering Detection

Xueting Yang, Zhong Li, changjun jiang, Wenbin Zhang and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

FENet: Functional Embedding Neural Network for Change-Point Detection in Functional Time Series

Caixia Xu, Jinhong You, Wen Li, shouguo du and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

The BV4 Benchmark for Unsupervised Anomaly Detection in High-Dimensional Spectral Data Streams

Nicolas Rojas Varela, Julien Ah-Pine, Engelbert Mephu Nguifo

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

PRISM: Asymmetric Precision-Recall Optimization for Million-Scale Root Cause Analysis

Wei Zhang, Rongyao Cai, Xiaosheng Li, Hang Yu and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

Distilling Multi-Teacher Scoring Principles for Unsupervised Time Series Anomaly Detection

Dongchan Cho, Jiho Han, Juwon Hwang, Changhee Min and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

TENET: Time-point Encoding Network for Multivariate Time Series Anomaly Detection

Dongchan Cho, Juwon Hwang, Keumyeong Kang, Jiho Han and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Online Bayesian Calibration under Gradual and Abrupt System Changes

BRPC enables online Bayesian calibration under nonstationarity by separating particle-based parameter updates from discrepancy updates, with restart mechanisms for abrupt regime shifts, improving accuracy over baselines.

Yang Xu, Chiwoo Park

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

VETime: Vision Enhanced Zero-Shot Time Series Anomaly Detection

VETime unifies temporal and visual modalities via fine-grained alignment and dynamic fusion for zero-shot time-series anomaly detection, outperforming state-of-the-art models with lower overhead.

Yingyuan Yang, Tian Lan, Yifei Gao, Yimeng Lu and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

VACE: Learning Geometrically Structured Representations for Time Series Anomaly Detection

VACE learns geometrically structured time-series embeddings via velocity consistency to detect anomalies with state-of-the-art accuracy on TSB-AD-M.

Alberto D Cencillo, Leonardo Concepción, Isaac Triguero, Julián Luengo

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

Progressive Risk Estimation for Accident Anticipation

PRE-ACT models accident risk as a continuously evolving signal that increases approaching crashes, enforcing temporal ordering and distance awareness to suppress false alarms and improve anticipation performance.

Samet Hicsonmez, Eray Çakar, Nermin Samet, Fatma Guney

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

PICID: A Modular Evaluation Infrastructure for Reproducible PHM Across Tasks and Domains

PICID introduces a modular infrastructure that formalizes reproducible PHM evaluation pipelines and enables fair cross-task comparisons across diagnostics and prognostics.

Lev Telyatnikov, Raffael Theiler, Leandro Von Krannichfeldt, Olga Fink

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Where Root Cause Analysis Fails: A Retrieval-Reranking Decomposition

Root cause analysis benchmarks conflate retrieval and reranking failures, revealing graph methods rarely beat statistical baselines; a two-stage retriever-LLM reranker matches or exceeds all baselines without causal graphs or labels.

Hada M Muhammad, Luan Pham, Laure Barrière, Sachin Shetty and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Tiny but Trusted: Efficient Vision-Language Reasoning for Time-Series Anomaly Detection

VisAnomReasoner is a parameter-efficient vision-language model that improves time-series anomaly detection precision and F1 by over 21 points via VisAnomBench fine-tuning with natural-language rationales.

Xiaona Zhou, Tianjiao (Joey) Yu, Muntasir Wahed, Constantin Brif and 1 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 2 on Hugging Face

COMET: Codebook-based Online-adaptive Multi-scale Embedding for Time-series Anomaly Detection

COMET uses multi-scale patch encoding, vector-quantized codebooks, and online adaptation to detect time-series anomalies, achieving best performance on 36 of 45 metrics.

JINWOO PARK, Hyeongwon Kang, Seung H Han, Pilsung Kang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

In-context learning to predict critical transitions in dynamical systems

TipPFN uses in-context learning to robustly predict critical transitions in unseen dynamical regimes and real-world data from limited, noisy observations.

Yunus Sevinchan, Juan Nathaniel, Kai Ueltzhöffer, Carla Roesch and 7 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026