7 citations · 18 across the 50 of their papers we have counts for
12 papers · 1 filter
Exploring Coding Spot: Understanding Parametric Contributions to LLM Coding Performance
Dongjun Kim, Minhyuk Kim, YongChan Chun +2
Large Language Models (LLMs) have demonstrated notable proficiency in both code generation and comprehension across multiple programming languages. However, the mechanisms underlyi…
ChatLang-8: An LLM-Based Synthetic Data Generation Framework for Grammatical Error Correction
Jeiyoon Park, Chanjun Park, Heuiseok Lim
We explore and improve the capabilities of LLMs to generate data for grammatical error correction (GEC). When merely producing parallel sentences, their patterns are too simplistic…
Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark
Chanjun Park, Hyeonwoo Kim, Dahyun Kim +5
This paper introduces the Open Ko-LLM Leaderboard and the Ko-H5 Benchmark as vital tools for evaluating Large Language Models (LLMs) in Korean. Incorporating private test sets whil…
CharacterGPT: A Persona Reconstruction Framework for Role-Playing Agents
Jeiyoon Park, Chanjun Park, Heuiseok Lim
The recent introduction of the Assistants API highlights its potential for large language models (LLMs) in role-playing agents (RPA). However, maintaining consistent character pers…
Translation of Multifaceted Data without Re-Training of Machine Translation Systems
Hyeonseok Moon, Seungyoon Lee, Seongtae Hong +3
Translating major language resources to build minor language resources becomes a widely-used approach. Particularly in translating complex data points composed of multiple componen…
SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models
Hyeonwoo Kim, Gyoungjin Gim, Yungi Kim +4
This study presents a novel learning approach designed to enhance both mathematical reasoning and problem-solving abilities of Large Language Models (LLMs). We focus on integrating…
Evalverse: Unified and Accessible Library for Large Language Model Evaluation
Jihoo Kim, Wonho Song, Dahyun Kim +3
This paper introduces Evalverse, a novel library that streamlines the evaluation of Large Language Models (LLMs) by unifying disparate evaluation tools into a single, user-friendly…
Model-Based Data-Centric AI: Bridging the Divide Between Academic Ideals and Industrial Pragmatism
Chanjun Park, Minsoo Khang, Dahyun Kim
This paper delves into the contrasting roles of data within academic and industrial spheres, highlighting the divergence between Data-Centric AI and Model-Agnostic AI approaches. W…
Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models
Hyunbyung Park, Sukyung Lee, Gyoungjin Gim +3
To address the challenges associated with data processing at scale, we propose Dataverse, a unified open-source Extract-Transform-Load (ETL) pipeline for large language models (LLM…
sDPO: Don't Use Your Data All at Once
Dahyun Kim, Yungi Kim, Wonho Song +4
As development of large language models (LLM) progresses, aligning them with human preferences has become increasingly important. We propose stepwise DPO (sDPO), an extension of th…
Toward Practical Automatic Speech Recognition and Post-Processing: a Call for Explainable Error Benchmark Guideline
Seonmin Koo, Chanjun Park, Jinsung Kim +4
Automatic speech recognition (ASR) outcomes serve as input for downstream tasks, substantially impacting the satisfaction level of end-users. Hence, the diagnosis and enhancement o…
Alternative Speech: Complementary Method to Counter-Narrative for Better Discourse
Seungyoon Lee, Dahyun Jung, Chanjun Park +2
We introduce the concept of "Alternative Speech" as a new way to directly combat hate speech and complement the limitations of counter-narrative. An alternative speech provides pra…