6 citations · 13 across the 15 of their papers we have counts for
15 papers
TextME: Bridging Unseen Modalities Through Text Descriptions
Soyeon Hong, Jinchan Kim, Jaegook You +3
Expanding multimodal representations to novel modalities is constrained by reliance on large-scale paired datasets (e.g., text-image, text-audio, text-3D, text-molecule), which are…
Trillion 7B Technical Report
Sungjun Han, Juyoung Suk, Suyeong An +5
We introduce Trillion-7B, the most token-efficient Korean-centric multilingual LLM available. Our novel Cross-lingual Document Attention (XLDA) mechanism enables highly efficient a…
Towards Fully-Automated Materials Discovery via Large-Scale Synthesis Dataset and Expert-Level LLM-as-a-Judge
Heegyu Kim, Taeyang Jeon, Seungtaek Choi +12
Materials synthesis is vital for innovations such as energy storage, catalysis, electronics, and biomedical devices. Yet, the process relies heavily on empirical, trial-and-error m…
FLEX: Expert-level False-Less EXecution Metric for Reliable Text-to-SQL Benchmark
Heegyu Kim, Taeyang Jeon, Seunghwan Choi +2
Text-to-SQL systems have become crucial for translating natural language into SQL queries in various industries, enabling non-technical users to perform complex data operations. Th…
Interventional Speech Noise Injection for ASR Generalizable Spoken Language Understanding
Yeonjoon Jung, Jaeseong Lee, Seungtaek Choi +3
Recently, pre-trained language models (PLMs) have been increasingly adopted in spoken language understanding (SLU). However, automatic speech recognition (ASR) systems frequently p…
Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models
Seungduk Kim, Seungtaek Choi, Myeongho Jeong
This report introduces \texttt{EEVE-Korean-v1.0}, a Korean adaptation of large language models that exhibit remarkable capabilities across English and Korean text understanding. Bu…
Addressing Cold Start Problem for End-to-end Automatic Speech Scoring
Jungbae Park, Seungtaek Choi
Integrating automatic speech scoring/assessment systems has become a critical aspect of second-language speaking education. With self-supervised learning advancements, end-to-end s…
Multi-Architecture Multi-Expert Diffusion Models
Yunsung Lee, Jin-Young Kim, Hyojun Go +3
In this paper, we address the performance degradation of efficient diffusion models by introducing Multi-architecturE Multi-Expert diffusion models (MEME). We identify the need for…
ScoreCL: Augmentation-Adaptive Contrastive Learning via Score-Matching Function
Jin-Young Kim, Soonwoo Kwon, Hyojun Go +3
Self-supervised contrastive learning (CL) has achieved state-of-the-art performance in representation learning by minimizing the distance between positive pairs while maximizing th…
Addressing Negative Transfer in Diffusion Models
Hyojun Go, JinYoung Kim, Yunsung Lee +4
Diffusion-based generative models have achieved remarkable success in various domains. It trains a shared model on denoising tasks that encompass different noise levels simultaneou…
Cross Encoding as Augmentation: Towards Effective Educational Text Classification
Hyun Seung Lee, Seungtaek Choi, Yunsung Lee +5
Text classification in education, usually called auto-tagging, is the automated process of assigning relevant tags to educational content, such as questions and textbooks. However,…
Evaluation of Question Generation Needs More References
Shinhyeok Oh, Hyojun Go, Hyeongdon Moon +4
Question generation (QG) is the task of generating a valid and fluent question based on a given context and the target answer. According to various purposes, even given the same co…
Towards Zero-Shot Functional Compositionality of Language Models
Hangyeol Yu, Myeongho Jeong, Jamin Shin +3
Large Pre-trained Language Models (PLM) have become the most desirable starting point in the field of NLP, as they have become remarkably good at solving many individual tasks. Des…
Towards Practical Plug-and-Play Diffusion Models
Hyojun Go, Yunsung Lee, Jin-Young Kim +4
Diffusion-based generative models have achieved remarkable success in image generation. Their guidance formulation allows an external model to plug-and-play control the generation…
Evaluating the Knowledge Dependency of Questions
Hyeongdon Moon, Yoonseok Yang, Jamin Shin +6
The automatic generation of Multiple Choice Questions (MCQ) has the potential to reduce the time educators spend on student assessment significantly. However, existing evaluation m…