Scholar
Hakaze Cho
Google Scholar ID: q_eQAcwAAAAJ
PhD Student, Japan Advanced Institute of Science and Technology
Machine Learning
Interpretability
In-context Learning
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Citations & Impact
All-time
Citations
43
H-index
4
i10-index
1
Publications
19
Co-authors
10
list available
Publications
12 items
Rethinking Contextualization by Reinterpreting Attention Head Channels
2026
Cited
0
Task Vectors, Learned Not Extracted: Performance Gains and Mechanistic Insight
2025
Cited
0
Localizing Task Recognition and Task Learning in In-Context Learning via Attention Head Analysis
2025
Cited
0
Mechanism of Task-oriented Information Removal in In-context Learning
2025
Cited
0
Binary Autoencoder for Mechanistic Interpretability of Large Language Models
2025
Cited
0
Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning
2025
Cited
0
Mechanistic Fine-tuning for In-context Learning
2025
Cited
0
Affinity and Diversity: A Unified Metric for Demonstration Selection via Internal Representations
2025
Cited
0
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Co-authors
10 total
Naoya Inoue
Japan Advanced Institute of Science and Technology (JAIST) / RIKEN AIP
Mariko Kato
Japan Advanced Institute of Science and Technology
Haolin Yang
University of Chicago
Tetsushi Ohki
College of Informatics, Shizuoka University
Yiqiao Zhong
Assistant Professor, University of Wisconsin--Madison
Gouki Minegishi
University of Tokyo
Kaize Ding
Assistant Professor of Stats & Data Science, Northwestern University
Kentaro Inui
MBZUAI, Tohoku University, RIKEN
