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From the 1 of 9 linked papers with an AI index.

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9 papers

cs.CL2026

MJ: Multi-turn LLM Jailbreaking via Decomposed Credit Assignment

Junyoung Park, Namgyu Park, Sechan Lee +3

The paper proposes a turn-level credit assignment framework (DC‑GRPO) for training multi‑turn jailbreak attacks on large language models, showing higher success rates than prior me…

cs.CR2026

REAN: Reconstruction-aware ECG Anonymization Based on Privacy--Utility Orthogonality

Taerin Ki, Sunghwan Park, Junyoung Park +1

A shared electrocardiogram (ECG) is itself a biometric fingerprint that can re-identify a patient and reveal personal information. Recent ECG anonymizers transform the signal befor…

cs.CR2026

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

Junyoung Park, Seongyong Ju, Sunghwan Park +1

As Large Language Models evolve for user convenience, vulnerability to jailbreak attacks continues to be reported despite ongoing efforts in safety training. Traditional jailbreak…

cs.AI2026

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

Junyoung Park, Sunghwan Park, Seongyong Ju +1

Attack Success Rate (ASR) evaluates each jailbreak with a single yes/no label at the end of generation, telling us whether a failure happened but not how it unfolded. Two attacks t…

cs.LG2026

QUOKA: Query-Oriented KV Selection For Efficient LLM Prefill

Dalton Jones, Junyoung Park, Matthew Morse +3

We present QUOKA: Query-oriented KV selection for efficient attention, a training-free and hardware agnostic sparse attention algorithm for accelerating transformer inference under…

cs.LG2026

Fast Forward: Accelerating LLM Prefill with Predictive FFN Sparsity

Aayush Gautam, Mukul Gagrani, Junyoung Park +3

The prefill stage of large language model (LLM) inference is a key computational bottleneck for long-context workloads. At short-to-moderate context lengths (1K--16K tokens), Feed-…