# From Zero to Hero: Cold-Start Anomaly Detection

Source: [From Zero to Hero: Cold-Start Anomaly Detection](<https://www.sota2.com/research/paper/68fa73601e209131cea5c0a8>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-02T06:05:11.801Z

Authors: Tal Reiss, George Kour, Naama Zwerdling, Ateret Anaby-Tavor, Yedid Hoshen

Published: 2024-05-30T17:59:51.000Z

## Abstract

When first deploying an anomaly detection system, e.g., to detect out-of-scope queries in chatbots, there are no observed data, making data-driven approaches ineffective. Zero-shot anomaly detection methods offer a solution to such "cold-start" cases, but unfortunately they are often not accurate enough. This paper studies the realistic but underexplored cold-start setting where an anomaly detection model is initialized using zero-shot guidance, but subsequently receives a small number of contaminated observations (namely, that may include anomalies). The goal is to make efficient use of both the zero-shot guidance and the observations. We propose ColdFusion, a method that effectively adapts the zero-shot anomaly detector to contaminated observations. To support future development of this new setting, we propose an evaluation suite consisting of evaluation protocols and metrics.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Out-of-scope Intent Detection on CLINC-Banking (C-Bank) r=2.5% contamination (test)](<https://www.sota2.com/research/sota/out-of-scope-intent-detection-on-clinc-banking-c-bank-r-2-5-percent-contamination-test.md>): Out-of-scope Intent Detection; CLINC-Banking (C-Bank) r=2.5% contamination (test); AUC (10% Contamination): 87.

- [Out-of-scope intent detection on CLINC-CreditCards OOS (test)](<https://www.sota2.com/research/sota/out-of-scope-intent-detection-on-clinc-creditcards-oos-test.md>): Out-of-scope Intent Detection; CLINC-CreditCards OOS (test); AUC (10% Threshold): 86.4.

- [Out-of-scope Intent Detection on CLINC-Cards (C-Cards) r=2.5% contamination (test)](<https://www.sota2.com/research/sota/out-of-scope-intent-detection-on-clinc-cards-c-cards-r-2-5-percent-contamination-test.md>): Out-of-scope Intent Detection; CLINC-Cards (C-Cards) r=2.5% contamination (test); AUC2 (10%): 85.2.

- [Out-of-Scope Query Detection on Banking77-OOS (test)](<https://www.sota2.com/research/sota/out-of-scope-query-detection-on-banking77-oos-test.md>): Out-of-Scope Query Detection; Banking77-OOS (test); AUC^2 (10%): 83.3.

- [Out-of-Scope Query Detection on CLINC-Banking (C-Bank) (test)](<https://www.sota2.com/research/sota/out-of-scope-query-detection-on-clinc-banking-c-bank-test.md>): Out-of-Scope Query Detection; CLINC-Banking (C-Bank) (test); AUC (10% Threshold): 84.4.

- [Out-of-scope Intent Detection on Banking77 (r=2.5% contamination, test)](<https://www.sota2.com/research/sota/out-of-scope-intent-detection-on-banking77-r-2-5-percent-contamination-test.md>): Out-of-scope Intent Detection; Banking77 (B77) r=2.5% contamination (test); AUC2 (10% Subset): 0.806.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2405.20341>)

[PDF](<https://arxiv.org/pdf/2405.20341.pdf>)

[Implementation](<https://github.com/talreiss/ColdFusion>)
