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Luke Ong

AAAI 2026ACL 2026ICML 2026可解释性多模态检索与知识
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0 一作 · 3 篇 · AAAI 2026 / ACL 2026 / ICML 2026

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2026 顶会论文

3
作者位次 #5/5ICML 2026Poster· General Machine Learning / Supervised Learning

When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer

Shuqi Liu · Yuzhou Cao · Lei Feng · Bo An · Luke Ong

作者位次 #4/4ACL 2026Workshop· ACL System Demonstrations

Spectra: A Mechanistic Interpretability Library for Vision-Language Models

Clement Neo · Yongsen Zheng · Kwok Yan Lam · Luke Ong

摘要

Vision-Language Models (VLMs) have become increasingly important in AI applications, yet interpretability tools for these models lag behind those available for text-only language models. While libraries like TransformerLens have enabled significant progress in understanding language models, exist...

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