activity
20222026
most citedHyperCLOVA X Technical Report

7 citations · 26 across the 25 of their papers we have counts for

collaborators

25 papers

cs.CY2026

Human-AI Co-Creativity: Advances, Opportunities, and Challenges

Adish Singla, Abhilasha Ravichander, Liwei Jiang +7

This survey article has grown out of the human-AI co-creativity workshop organized by the authors at the ICML 2026 conference. We organized this workshop as part of a community-bui…

cs.CV2026

Investigating Social Bias in Narrative Image Generation

Junyeong Park, Sowon Min, Euna Jang +5

Text-to-image (T2I) generation models are increasingly embedded in applications such as media content creation and education, raising concerns about how their outputs may reproduce…

cs.CL2026

Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability

Alicia Parrish, Rajat Shinde, Sanket Badhe +57

Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances,…

cs.CL2026

JuICE: A Benchmark for Evaluating LLM-Judge in Identifying Cultural Errors

Jiho Jin, Junho Myung, Juhyun Oh +5

As large language models (LLMs) are increasingly deployed to users around the world, they are integrated into everyday tasks across diverse cultural contexts, from drafting persona…

cs.CL2026

SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures

Nedjma Ousidhoum, Junho Myung, Carla Perez-Almendros +27

We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an extended version of our manual…

cs.CL2026

FINEST: Improving LLM Responses to Sensitive Topics Through Fine-Grained Evaluation

Juhyun Oh, Nayeon Lee, Chani Jung +5

Large Language Models (LLMs) often generate overly cautious and vague responses on sensitive topics, sacrificing helpfulness for safety. Existing evaluation frameworks lack systema…

cs.CV2025

World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models

Eunsu Kim, Junyeong Park, Na Min An +9

In a globalized world, cultural elements from diverse origins frequently appear together within a single visual scene. We refer to these as culture mixing scenarios, yet how Large…

cs.CL2025

Open Korean Historical Corpus: A Millennia-Scale Diachronic Collection of Public Domain Texts

Seyoung Song, Nawon Kim, Songeun Chae +5

The history of the Korean language is characterized by a discrepancy between its spoken and written forms and a pivotal shift from Chinese characters to the Hangul alphabet. Howeve…

cs.CL2025

Gradual Code-Switching as Inference-Time Cross-Lingual Representational Alignment for LLMs

Haneul Yoo, Jiho Jin, Kyunghyun Cho +1

While large language models (LLMs) have achieved notable progress in multilingual settings, their performance remains uneven across languages as LLMs often rely on English-centric…

cs.CL2025

CulTrace: Tracing Internal Cultural Reasoning in Large Language Models

Haeun Yu, Arnav Arora, Seogyeong Jeong +7

The growing deployment of large language models (LLMs) across diverse cultural contexts necessitates a deeper understanding of models' hidden representations of different cultures.…

cs.CL2025

MUG-Eval: A Proxy Evaluation Framework for Multilingual Generation Capabilities in Any Language

Seyoung Song, Seogyeong Jeong, Eunsu Kim +4

Evaluating text generation capabilities of large language models (LLMs) is challenging, particularly for low-resource languages where methods for direct assessment are scarce. We p…

cs.CL2025

Social Bias Benchmark for Generation: A Comparison of Generation and QA-Based Evaluations

Jiho Jin, Woosung Kang, Junho Myung +1

Measuring social bias in large language models (LLMs) is crucial, but existing bias evaluation methods struggle to assess bias in long-form generation. We propose a Bias Benchmark…

cs.CL2025★ 1 cited

HERITAGE: An End-to-End Web Platform for Processing Korean Historical Documents in Hanja

Seyoung Song, Haneul Yoo, Jiho Jin +2

While Korean historical documents are invaluable cultural heritage, understanding those documents requires in-depth Hanja expertise. Hanja is an ancient language used in Korea befo…

cs.CL2024

Shared Heritage, Distinct Writing: Rethinking Resource Selection for East Asian Historical Documents

Seyoung Song, Haneul Yoo, Jiho Jin +2

Historical documents in the Sinosphere are known to share common formats and practices, particularly in veritable records compiled by court historians. This shared linguistic herit…

cs.CL2024★ 2 cited

Survey of Cultural Awareness in Language Models: Text and Beyond

Siddhesh Pawar, Junyeong Park, Jiho Jin +7

Large-scale deployment of large language models (LLMs) in various applications, such as chatbots and virtual assistants, requires LLMs to be culturally sensitive to the user to ens…

cs.CL2024

Perceptions to Beliefs: Exploring Precursory Inferences for Theory of Mind in Large Language Models

Chani Jung, Dongkwan Kim, Jiho Jin +5

While humans naturally develop theory of mind (ToM), the capability to understand other people's mental states and beliefs, state-of-the-art large language models (LLMs) underperfo…

cs.CL2024★ 5 cited

BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

Junho Myung, Nayeon Lee, Yi Zhou +19

Large language models (LLMs) often lack culture-specific knowledge of daily life, especially across diverse regions and non-English languages. Existing benchmarks for evaluating LL…

cs.CL2024★ 7 cited

HyperCLOVA X Technical Report

Kang Min Yoo, Jaegeun Han, Sookyo In +393

We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…

cs.HC2023★ 2 cited

Learning from Teaching Assistants to Program with Subgoals: Exploring the Potential for AI Teaching Assistants

Changyoon Lee, Junho Myung, Jieun Han +2

With recent advances in generative AI, conversational models like ChatGPT have become feasible candidates for TAs. We investigate the practicality of using generative AI as TAs in…

cs.CL2023

Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysis

Nayeon Lee, Chani Jung, Junho Myung +4

Warning: this paper contains content that may be offensive or upsetting. Most hate speech datasets neglect the cultural diversity within a single language, resulting in a critical…

cs.CL2023★ 2 cited

KoBBQ: Korean Bias Benchmark for Question Answering

Jiho Jin, Jiseon Kim, Nayeon Lee +3

The Bias Benchmark for Question Answering (BBQ) is designed to evaluate social biases of language models (LMs), but it is not simple to adapt this benchmark to cultural contexts ot…

cs.CL2022★ 7 cited

HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea

Haneul Yoo, Jiho Jin, Juhee Son +3

Historical records in Korea before the 20th century were primarily written in Hanja, an extinct language based on Chinese characters and not understood by modern Korean or Chinese…

cs.LG2022

Models and Benchmarks for Representation Learning of Partially Observed Subgraphs

Dongkwan Kim, Jiho Jin, Jaimeen Ahn +1

Subgraphs are rich substructures in graphs, and their nodes and edges can be partially observed in real-world tasks. Under partial observation, existing node- or subgraph-level mes…

cs.CL2022

Two-Step Question Retrieval for Open-Domain QA

Yeon Seonwoo, Juhee Son, Jiho Jin +4

The retriever-reader pipeline has shown promising performance in open-domain QA but suffers from a very slow inference speed. Recently proposed question retrieval models tackle thi…