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Home/Authors/Christopher Leckie

Christopher Leckie

2 indexed papers

Recent (6 mo)
2
With code
0
Influential cites
0
Benchmarked
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Publications per year

2
26

Top categories

ML×2AI×1Vision×1Crypto×1

Frequent co-authors

Hesam Asadollahzadeh1×
Feng Liu1×
Sarah M. Erfani1×
Hugo Lyons Keenan1×
Sarah Erfani1×

Research Timeline

2026
Mechanistic Anomaly Detection via Functional Attribution

The paper proposes reframing mechanistic anomaly detection (MAD) as a functional attribution problem, using influence functions to measure how much a model's output depends on specific input samples, achieving state-of-the-art results across various anomaly types and modalities.

TRACER: Persistent Regularization for Robust Multimodal Finetuning

The paper introduces TRACER, a novel regularization framework that uses Weighted Moving Average (WMA) distillation to robustly finetune multimodal models, mitigating catastrophic forgetting and improving out-of-distribution performance.

Highlighted terms show continued research focus across papers

Papers

cs.LGcs.AIcs.CVRecentMay 28, 2026

TRACER: Persistent Regularization for Robust Multimodal Finetuning

Hesam Asadollahzadeh, Feng Liu, Christopher Leckie, Sarah M. Erfani

The paper introduces TRACER, a novel regularization framework that uses Weighted Moving Average (WMA) distillation to robustly finetune multimodal models, mitigating catastrophic forgetting and improv…

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cs.LGcs.CRRecentApr 21, 2026

Mechanistic Anomaly Detection via Functional Attribution

Hugo Lyons Keenan, Christopher Leckie, Sarah Erfani

The paper proposes reframing mechanistic anomaly detection (MAD) as a functional attribution problem, using influence functions to measure how much a model's output depends on specific input samples,…

View →