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20232026
most citedPersona is a Double-edged Sword: Mitigating the Negative Impact of Role-playing Prompts in Zero-shot Reasoning Tasks

2 citations · 4 across the 16 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Personalized Privacy Control in LLMs via Attention Head Intervention

Junseok Kim, Nakyeong Yang, Kyomin Jung

The rise of agentic AI enables LLMs to access diverse user data, raising critical privacy concerns. Prior work on contextual privacy studies whether LLMs regulate information discl…

cs.CL2026

Are We Measuring Strategy or Phrasing? The Gap Between Surface- and Approach-Level Diversity in LLM Math Reasoning

Sangmook Lee, Minbeom Kim, Jeonghye Kim +3

Diversity in LLM mathematical reasoning is critical for exploration, but common diversity metrics mostly capture surface-level variation rather than differences in how a problem is…

cs.CL2026

How You Ask Matters! Adaptive RAG Robustness to Query Variations

Yunah Jang, Megha Sundriyal, Kyomin Jung +1

Adaptive Retrieval-Augmented Generation (RAG) promises accuracy and efficiency by dynamically triggering retrieval only when needed and is widely used in practice. However, real-wo…

cs.CL2026

Beyond Normalization: Rethinking the Partition Function as a Difficulty Scheduler for RLVR

Dohyung Kim, Minbeom Kim, Jeonghye Kim +3

Reward-maximizing RL methods have shown to be capable of enhancing the reasoning performance of LLMs, but often lead to reduced generation diversity. Recent works address this issu…

cs.CL2026

Persona Switch: Mixing Distinct Perspectives in Decoding Time

Junseok Kim, Nakyeong Yang, Kyomin Jung

Role-play prompting is known to steer the behavior of language models by injecting a persona into the prompt, improving their zero-shot reasoning capabilities. However, such improv…

cs.CL2026

Reliability-Aware Adaptive Self-Consistency for Efficient Sampling in LLM Reasoning

Junseok Kim, Nakyeong Yang, Kyungmin Min +1

Self-Consistency improves reasoning reliability through multi-sample aggregation, but incurs substantial inference cost. Adaptive self-consistency methods mitigate this issue by ad…