5 papers
NaturalFlow: Reducing Disruptive Pauses for Natural Speech Flow in Simultaneous Speech-to-Speech Translation
Dongwook Lee, Youngho Cho, Sangkwon Park +2
Simultaneous speech-to-speech translation aims to enable near-real-time communication by minimizing latency, offering a compelling, real-time alternative to the high latency of con…
Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization
Yeongtak Oh, Dongwook Lee, Sangkwon Park +2
While multimodal large language models have advanced across text, image, and audio, personalization research has remained primarily vision-language, with unified omnimodal benchmar…
Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning
Sangkwon Park, Donghun Kang, Jisoo Mok +1
The conventional Retrieval-Augmented Generation (RAG) paradigm of injecting raw retrieved texts into the Large Language Model (LLM)'s context often results in suboptimal integratio…
Exploring the Potential of LLMs as Personalized Assistants: Dataset, Evaluation, and Analysis
Jisoo Mok, Ik-hwan Kim, Sangkwon Park +1
Personalized AI assistants, a hallmark of the human-like capabilities of Large Language Models (LLMs), are a challenging application that intertwines multiple problems in LLM resea…
Does Your Voice Assistant Remember? Analyzing Conversational Context Recall and Utilization in Voice Interaction Models
Heeseung Kim, Che Hyun Lee, Sangkwon Park +4
Recent advancements in multi-turn voice interaction models have improved user-model communication. However, while closed-source models effectively retain and recall past utterances…