2 citations · 2 across the 9 of their papers we have counts for
10 papers
Causal Behavioral Evaluation of AI Agents at Scale via Automated Behavioral Science
Soo Yong Lee, Jongha Lee, Jaewan Chun +8
As AI agents are increasingly deployed in complex and new environments, knowing the conditions that influence their behavior becomes an indispensable step for their reliable and sa…
Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook
Jaehyeok Lee, Xiaoyuan Yi, Jing Yao +4
As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks face the Construct-Composition-Co…
Personalized Parameter-Efficient Fine-Tuning of Foundation Models for Multimodal Recommendation
Sunwoo Kim, Hyunjin Hwang, Kijung Shin
In recent years, substantial research has integrated multimodal item metadata into recommender systems, often by using pre-trained multimodal foundation models to encode such data.…
Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption
Sunwoo Kim, Soo Yong Lee, Kyungho Kim +3
Unsupervised node representation learning aims to obtain meaningful node embeddings without relying on node labels. To achieve this, graph convolution, which aggregates information…
Learning to Flow from Generative Pretext Tasks for Neural Architecture Encoding
Sunwoo Kim, Hyunjin Hwang, Kijung Shin
The performance of a deep learning model on a specific task and dataset depends heavily on its neural architecture, motivating considerable efforts to rapidly and accurately identi…
HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search
Hyunjin Choo, Fanchen Bu, Hyunjin Hwang +2
Higher-order interactions (HOIs) in complex systems, such as scientific collaborations, multi-protein complexes, and multi-user communications, are commonly modeled as hypergraphs,…
Emergence of psychopathological computations in large language models
Soo Yong Lee, Hyunjin Hwang, Taekwan Kim +5
Can large language models (LLMs) instantiate computations of psychopathology? In this work, we establish a computational-theoretical framework to provide an account of psychopathol…
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications
Hyeonsoo Jo, Hyunjin Hwang, Fanchen Bu +3
Adversarial attacks are allegedly unnoticeable. Prior studies have designed attack noticeability measures on graphs, primarily using statistical tests to compare the topology of or…
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang +1
Recently, many deep-learning techniques have been applied to various weather-related prediction tasks, including precipitation nowcasting (i.e., predicting precipitation levels and…
AHP: Learning to Negative Sample for Hyperedge Prediction
Hyunjin Hwang, Seungwoo Lee, Chanyoung Park +1
Hypergraphs (i.e., sets of hyperedges) naturally represent group relations (e.g., researchers co-authoring a paper and ingredients used together in a recipe), each of which corresp…