5 papers
PRAGMA: Evaluating Personalized Guidance with Memory Alignment in Lifelong Conversations
Hyojeong Yu, Hyukhun Koh, Minsung Kim +2
Large language models (LLMs) are increasingly deployed as personalized assistants that interact with users over extended periods of time. As conversations grow longer, relying on f…
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…
Unplug and Play Language Models: Decomposing Experts in Language Models at Inference Time
Nakyeong Yang, Jiwon Moon, Junseok Kim +2
Enabled by large-scale text corpora with huge parameters, pre-trained language models operate as multi-task experts using a single model architecture. However, recent studies have…
MP2D: An Automated Topic Shift Dialogue Generation Framework Leveraging Knowledge Graphs
Yerin Hwang, Yongil Kim, Yunah Jang +3
Despite advancements in on-topic dialogue systems, effectively managing topic shifts within dialogues remains a persistent challenge, largely attributed to the limited availability…
IterCQR: Iterative Conversational Query Reformulation with Retrieval Guidance
Yunah Jang, Kang-il Lee, Hyunkyung Bae +2
Conversational search aims to retrieve passages containing essential information to answer queries in a multi-turn conversation. In conversational search, reformulating context-dep…