activity
20232026
most citedMini-Batch Optimization of Contrastive Loss

2 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

eess.AS2026

Raon-OpenTTS: Open Models and Data for Robust Text-to-Speech

Semin Kim, Seungjun Chung, Taehong Moon +8

Recent advances in text-to-speech (TTS) models show impressive speech naturalness and quality, yet the role of large-scale open data in driving this progress remains underexplored.…

cs.CL2026

Raon-Speech Technical Report

Beomsoo Kim, Changho Choi, Dohyun Kim +23

We present Raon-Speech, a top-performing 9B-parameter speech language model (SpeechLM) for English and Korean speech understanding, answering, and generation, and Raon-SpeechChat,…

cs.AI2025

Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games

Dongmin Park, Minkyu Kim, Beongjun Choi +13

Large Language Model (LLM) agents are reshaping the game industry, by enabling more intelligent and human-preferable characters. Yet, current game benchmarks fall short of practica…

cs.LG2024★ 1 cited

Efficient Generative Modeling with Residual Vector Quantization-Based Tokens

Jaehyeon Kim, Taehong Moon, Keon Lee +1

We introduce ResGen, an efficient Residual Vector Quantization (RVQ)-based generative model for high-fidelity generation with fast sampling. RVQ improves data fidelity by increasin…

eess.AS2024

DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors

Keon Lee, Dong Won Kim, Jaehyeon Kim +2

Large-scale latent diffusion models (LDMs) excel in content generation across various modalities, but their reliance on phonemes and durations in text-to-speech (TTS) limits scalab…

eess.AS2024★ 2 cited

CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech

Jaehyeon Kim, Keon Lee, Seungjun Chung +1

With the emergence of neural audio codecs, which encode multiple streams of discrete tokens from audio, large language models have recently gained attention as a promising approach…

cs.LG2023★ 2 cited

Mini-Batch Optimization of Contrastive Loss

Jaewoong Cho, Kartik Sreenivasan, Keon Lee +7

Contrastive learning has gained significant attention as a method for self-supervised learning. The contrastive loss function ensures that embeddings of positive sample pairs (e.g.…

cs.CV2023

Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback

TaeHo Yoon, Kibeom Myoung, Keon Lee +3

Diffusion models have recently shown remarkable success in high-quality image generation. Sometimes, however, a pre-trained diffusion model exhibits partial misalignment in the sen…