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cs.CL2026

DuplexGen: Adaptive Synthesis of Human-AI Turn-Taking Dialogues

Takyoung Kim, Kang-wook Kim, Sang Hoon Woo +3

Turn-taking is a central component of full-duplex interaction. Which turn-taking behaviors are appropriate varies with the scenario, yet current models apply a single norm regardle…

cs.CL2026

From Documents to Segments: A Contextual Reformulation for Topic Assignment

Hoonsang Yoon, Takyoung Kim, Wonkee Lee +3

Traditional topic modeling assigns a single topic to each document. In practice, however, many real-world documents, such as product reviews or open-ended survey responses, contain…

cs.CL2026

ReIn: Conversational Error Recovery with Reasoning Inception

Takyoung Kim, Jinseok Nam, Chandrayee Basu +5

Conversational agents powered by large language models (LLMs) with tool integration achieve strong performance on fixed task-oriented dialogue datasets but remain vulnerable to una…

cs.CL2025

Goal Alignment in LLM-Based User Simulators for Conversational AI

Shuhaib Mehri, Xiaocheng Yang, Takyoung Kim +3

User simulators are essential to conversational AI, enabling scalable agent development and evaluation through simulated interactions. While current Large Language Models (LLMs) ha…

cs.CL2025

AURA: A Diagnostic Framework for Tracking User Satisfaction of Interactive Planning Agents

Takyoung Kim, Janvijay Singh, Shuhaib Mehri +6

The growing capabilities of large language models (LLMs) in instruction-following and context-understanding lead to the era of agents with numerous applications. Among these, task…

cs.CL20251 cited

TD-EVAL: Revisiting Task-Oriented Dialogue Evaluation by Combining Turn-Level Precision with Dialogue-Level Comparisons

Emre Can Acikgoz, Carl Guo, Suvodip Dey +4

Task-oriented dialogue (TOD) systems are experiencing a revolution driven by Large Language Models (LLMs), yet the evaluation methodologies for these systems remain insufficient fo…