3 papers
cs.CL2026
Subject-level Inference for Realistic Text Anonymization Evaluation
Myeong Seok Oh, Dong-Yun Kim, Hanseok Oh +6
Current text anonymization evaluation relies on span-based metrics that fail to capture what an adversary could actually infer, and assumes a single data subject, ignoring multi-su…
cs.CV2025
Toward Reliable VLM: A Fine-Grained Benchmark and Framework for Exposure, Bias, and Inference in Korean Street Views
Xiaonan Wang, Bo Shao, Hansaem Kim
Recent advances in vision-language models (VLMs) have enabled accurate image-based geolocation, raising serious concerns about location privacy risks in everyday social media posts…
cs.CL2024
KULTURE Bench: A Benchmark for Assessing Language Model in Korean Cultural Context
Xiaonan Wang, Jinyoung Yeo, Joon-Ho Lim +1
Large language models have exhibited significant enhancements in performance across various tasks. However, the complexity of their evaluation increases as these models generate mo…