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Yo-Sub Han

37 papers hereh-index 690 citations49 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1
  • last author30

Across the 32 of 37 papers where every author was matched, so the position is known.

fields
  • cs.CL14
  • cs.AI11
  • cs.CR5
  • cs.SE4
  • cs.DS1
  • cs.NI1
same name
  • Yo-Sub Han — 10 papers, h 20
  • Yo-Sub Han — 4 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedATHENA: Mathematical Reasoning with Thought Expansion

2 citations · 4 across the 33 of their papers we have counts for

collaborators
Showing 2026 · cs.AIShow all

4 papers · 2 filters

cs.AI2026

One Adapter Pair per Model: A Universal Activation Interface for Language Models

Su-Hyeon Kim, Jiwan Mun, Yo-Sub Han

Activation-based tools are usually tied to one model's native hidden space, requiring probes, sparse autoencoders, and natural-language interpreters to be rebuilt or rediscovered f…

cs.AI2026

STAB: Specification-driven Testing for Algorithmic Bottlenecks

Soohan Lim, Joonghyuk Hahn, Hyundong Jin +1

Evaluating the efficiency of algorithmic code requires test cases that expose runtime bottlenecks. Previous methods generate efficiency test cases either by increasing input size o…

cs.AI2026

Cross-Family Universality of Behavioral Axes via Anchor-Projected Representations

Su-Hyeon Kim, Yo-Sub Han

Large language models from different families use different hidden dimensions, tokenizers, and training procedures, making behavioral directions difficult to compare or transfer ac…

cs.AI2026

How Does the Thinking Step Influence Model Safety? An Entropy-based Safety Reminder for LRMs

Su-Hyeon Kim, Hyundong Jin, Yejin Lee +1

Large Reasoning Models (LRMs) achieve remarkable success through explicit thinking steps, yet the thinking steps introduce a novel risk by potentially amplifying unsafe behaviors.…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.