Author

Seoyeon Lee

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#machine learning Preprint Sep 2026

Disentangling Spurious Correlations in Vision-Language-Action Models via Predicting Domain-Invariant Latent Lookahead

Vision-Language-Action (VLA) models remain brittle under visual distribution shifts, often relying on spurious correlations tied to domain-specific factors rather than task-relevant structure. We propose Domain-Invariant Latent Lookahead (DILL), a representation-learning framework that mitigates shortcut learning in VL...

Junghyun Kim, Ngseo Kim, Chung-Woo Lee et al. · 0 citations

#machine learning Jun 2026

The Interplay of Harness Design and Post-Training in LLM Agents

It is shown that harness-aware post-training not only improves in-distribution performance but also enables agents to robustly adapt to OOD settings, highlighting the importance of harness-aware post-training under such shifts.

Kyungmin Kim, Youngbin Choi, Seoyeon Lee et al. · arXiv.org · 7 citations