GITCO: Gated Inference-Time Context Optimization in TSFMs

[2606.05332] GITCO: Gated Inference-Time Context Optimization in TSFMs

[Submitted on 3 Jun 2026]

Title:GITCO: Gated Inference-Time Context Optimization in TSFMs

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Abstract:Patch-based Time Series Foundation Models (TSFMs) suffer from context poisoning: structurally anomalous patches capture disproportionate attention and silently degrade zero-shot forecast quality. We propose improving TSFM accuracy at inference time by optimizing the input context rather than modifying model weights. We present GITCO (Gated Inference-Time Context Optimization), a lightweight three-component framework: Gate, Router, and Critic that selectively identifies and suppresses harmful patches without any parameter updates. Evaluated on TimesFM 2.5 across 53 GIFT-Eval datasets under K-fold cross-validation, GITCO achieves an average +1.95% MASE reduction on TimesFM 2.5 while capturing 89.9% of the improvement upper bound. We introduce context sensitivity profiles as a new characterizable property of TSFMs: the mapping from time series meta-features to expected accuracy improvement under inference-time context intervention, shaped jointly by model architecture and the statistical structure of the data.

Comments: ICML 2026 Workshop on Foundation Models for Structured Data

Subjects:

Artificial Intelligence (cs.AI)

Cite as: arXiv:2606.05332 [cs.AI]

(or arXiv:2606.05332v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2606.05332

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Manya Pandey [view email] [v1] Wed, 3 Jun 2026 18:17:40 UTC (329 KB)

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