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20242026
most citedBLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

5 citations · 9 across the 18 of their papers we have counts for

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10 papers · 1 filter

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

Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues

Eunsu Kim, Junyeong Park, Juhyun Oh +5

As LLMs are increasingly deployed in real-world interactions, their social reasoning in interpersonal communication becomes critical. To explore their capabilities, we introduce SC…

cs.CL2025

RoleConflictBench: A Benchmark of Role Conflict Scenarios for Evaluating LLMs' Contextual Sensitivity

Jisu Shin, Hoyun Song, Juhyun Oh +4

People often encounter role conflicts -- social dilemmas where the expectations of multiple roles clash and cannot be simultaneously fulfilled. As large language models (LLMs) incr…

cs.CL2025

Spotting Out-of-Character Behavior: Atomic-Level Evaluation of Persona Fidelity in Open-Ended Generation

Jisu Shin, Juhyun Oh, Eunsu Kim +2

Ensuring persona fidelity in large language models (LLMs) is essential for maintaining coherent and engaging human-AI interactions. However, LLMs often exhibit Out-of-Character (OO…

cs.CL2025

Flex-TravelPlanner: A Benchmark for Flexible Planning with Language Agents

Juhyun Oh, Eunsu Kim, Alice Oh

Real-world planning problems require constant adaptation to changing requirements and balancing of competing constraints. However, current benchmarks for evaluating LLMs' planning…

cs.LG2025

Benchmarks Are Not Atomic: Composition-Aware LLM Evaluation using BenchHub

Eunsu Kim, Haneul Yoo, Guijin Son +3

LLM benchmarks are often treated as coherent measurement units, yet they are heterogeneous collections of instances spanning diverse domains, skills, formats, and contexts. As a re…

cs.CL2025

BLUCK: A Benchmark Dataset for Bengali Linguistic Understanding and Cultural Knowledge

Daeen Kabir, Minhajur Rahman Chowdhury Mahim, Sheikh Shafayat +4

In this work, we introduce BLUCK, a new dataset designed to measure the performance of Large Language Models (LLMs) in Bengali linguistic understanding and cultural knowledge. Our…

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

When Tom Eats Kimchi: Evaluating Cultural Bias of Multimodal Large Language Models in Cultural Mixture Contexts

Jun Seong Kim, Kyaw Ye Thu, Javad Ismayilzada +6

In a highly globalized world, it is important for multi-modal large language models (MLLMs) to recognize and respond correctly to mixed-cultural inputs. For example, a model should…

cs.CV2025★ 1 cited

Diffusion Models Through a Global Lens: Are They Culturally Inclusive?

Zahra Bayramli, Ayhan Suleymanzade, Na Min An +5

Text-to-image diffusion models have recently enabled the creation of visually compelling, detailed images from textual prompts. However, their ability to accurately represent vario…