9 papers
AI Engram: In Search of Memory Traces in Artificial Intelligence
Jea Kwon, Dong-Kyum Kim, Jiwon Kim +3
Memory formation is fundamental to intelligence, yet whether deep neural networks preserve identifiable memory traces analogous to biological memory units remains an open question.…
Textual Supervision Enhances Geospatial Representations in Vision-Language Models
Marcelo Sartori Locatelli, Fernando Tonucci, Jea Kwon +5
Geospatial understanding is a critical yet underexplored dimension in the development of machine learning systems for tasks such as image geolocation and spatial reasoning. In this…
Moir: Let the Model Direct Its Own Story for Robust Cross-Domain Knowledge Editing
Jea Kwon, Jiwon Kim, Dong-kyum Kim +1
While language models remain frozen at their training state, the world evolves continuously. Knowledge editing has emerged as a key alternative to full retraining, but its deployme…
Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions
Jiseon Kim, Jea Kwon, Luiz Felipe Vecchietti +3
Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decision-support systems, determini…
How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models
Minsung Kim, Dong-Kyum Kim, Jea Kwon +3
Large language models leverage both parametric knowledge acquired during pretraining and in-context knowledge provided at inference time. Crucially, when these sources conflict, mo…
Erase or Hide? Suppressing Spurious Unlearning Neurons for Robust Unlearning
Nakyeong Yang, Dong-Kyum Kim, Jea Kwon +3
Large language models trained on web-scale data can memorize private or sensitive knowledge, raising significant privacy risks. Although some unlearning methods mitigate these risk…