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Home/Authors/Sunghwan Park

Sunghwan Park

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×3Crypto×2

Frequent co-authors

Junyoung Park3×
Seongyong Ju3×
Jaewoo Lee3×

Research Timeline

2026
Beyond Attack Success Rate: Temporal Logit Observability for LLM Safety Failures

The paper introduces Temporal Logit Observability (TLO), a training-free diagnostic that analyzes the decoding process to reveal the temporal patterns of LLM safety failures, showing that failure mechanisms are often distinct even when the final Attack Success Rate is the same.

Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models

The paper introduces Persona Attack, a novel memory injection jailbreak method that demonstrates how accumulating instructions in the model's context window can override internal safety alignments, achieving high success rates.

Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models

The paper introduces Persona Attack, a novel memory injection jailbreak method that demonstrates that accumulating instructions in the model's context window can override internal safety alignments, achieving high attack success rates.

Highlighted terms show continued research focus across papers

Papers

cs.CRcs.AIRecentMay 29, 2026

Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models

Junyoung Park, Seongyong Ju, Sunghwan Park, Jaewoo Lee

The paper introduces Persona Attack, a novel memory injection jailbreak method that demonstrates how accumulating instructions in the model's context window can override internal safety alignments, ac…

View →
cs.CRcs.AIRecentMay 29, 2026

Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models

Junyoung Park, Seongyong Ju, Sunghwan Park, Jaewoo Lee

The paper introduces Persona Attack, a novel memory injection jailbreak method that demonstrates that accumulating instructions in the model's context window can override internal safety alignments, a…

View →
cs.AIRecentMay 28, 2026

Beyond Attack Success Rate: Temporal Logit Observability for LLM Safety Failures

Junyoung Park, Sunghwan Park, Seongyong Ju, Jaewoo Lee

The paper introduces Temporal Logit Observability (TLO), a training-free diagnostic that analyzes the decoding process to reveal the temporal patterns of LLM safety failures, showing that failure mech…

View →