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cs.CL2026

Overthinking Loops in Agents: A Structural Risk via MCP Tools

Yohan Lee, Jisoo Jang, Seoyeon Choi +2

Tool-using LLM agents increasingly coordinate real workloads by selecting and chaining third-party tools based on text-visible metadata such as tool names, descriptions, and return…

cs.CL2025

Finding Diamonds in Conversation Haystacks: A Benchmark for Conversational Data Retrieval

Yohan Lee, Yongwoo Song, Sangyeop Kim

We present the Conversational Data Retrieval (CDR) benchmark, the first comprehensive test set for evaluating systems that retrieve conversation data for product insights. With 1.6…

cs.CL2025

Pre-Storage Reasoning for Episodic Memory: Shifting Inference Burden to Memory for Personalized Dialogue

Sangyeop Kim, Yohan Lee, Sanghwa Kim +2

Effective long-term memory in conversational AI requires synthesizing information across multiple sessions. However, current systems place excessive reasoning burden on response ge…

cs.CL2025

EXPERT: An Explainable Image Captioning Evaluation Metric with Structured Explanations

Hyunjong Kim, Sangyeop Kim, Jongheon Jeong +2

Recent advances in large language models and vision-language models have led to growing interest in explainable evaluation metrics for image captioning. However, these metrics gene…

cs.CL2025

What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs

Sangyeop Kim, Yohan Lee, Yongwoo Song +1

We investigate long-context vulnerabilities in Large Language Models (LLMs) through Many-Shot Jailbreaking (MSJ). Our experiments utilize context length of up to 128K tokens. Throu…

cs.CL2025

LLM-guided Plan and Retrieval: A Strategic Alignment for Interpretable User Satisfaction Estimation in Dialogue

Sangyeop Kim, Sohhyung Park, Jaewon Jung +2

Understanding user satisfaction with conversational systems, known as User Satisfaction Estimation (USE), is essential for assessing dialogue quality and enhancing user experiences…