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Showing papers from Korea Institute of Science and Technology Show all papers

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NeurIPS 2026KoreaTelecom Paris, IP ParisKorea Institute of Science and TRepresentation & contrastive learning

Rethinking Attention in Depth for Operator Learning

Jaehyeon Lee, Kiwon Um, JungHyun Han, Min-Koo Kang

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

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57%Worth a look
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NeurIPS 2026Korea Institute of Science and TKAISTYonseiKorea Institute for Advanced StuImitation learning

Reconciling Safety and Performance via Dual-Expert Offline Imitation Learning

Seokin Seo, Sung Kuk Shyn, Minji Seo, Yisoo Lee and 3 more

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

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78%Highly rated
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NeurIPS 2026U MelbourneKorea Institute of Science and TVision-language models

FiLoRA: Focus-and-Ignore LoRA for Controllable Feature Reliance

FiLoRA is an instruction-conditioned LoRA framework that modulates multimodal model reliance on internal feature pathways via gated low-rank modules, enabling controllable amplification or suppression of feature groups without changing task semantics.

Hyunsuk Chung, Caren Han, Seungyeon Ji, Jinwoo Kim and 2 more

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

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 0/5