9 papers
Who's Behind the Text? Robust Model Authorship Attribution
Minseok Ko, Hyunseok Lee, Woomin Song +3
As large language models (LLMs) are increasingly used to generate text, their misuse has become a growing societal problem, with implications for academic misconduct, model distill…
Naive Visual Memory is Not Enough: A Failure-Mode Study of GUI Agents
Seoyoung Choi, Minseok Ko, Hyunseok Lee +4
Graphical User Interface (GUI) agents are increasingly used to automate complex computer tasks across applications, websites, and operating systems. To improve their reliability, r…
Benchmarking Visual State Tracking in Multimodal Video Understanding
Sihyun Yu, Nanye Ma, Pinzhi Huang +8
Understanding a video requires more than recognizing isolated moments, as humans continuously track entities, states, and events over time. This capacity for visual state tracking…
Cog3DMap: Multi-View Vision-Language Reasoning with 3D Cognitive Maps
Chanyoung Gwak, Yoonwoo Jeong, Byungwoo Jeon +3
Precise spatial understanding from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs), as their visual representations are predominantly…
Beyond Correctness: Learning Robust Reasoning via Transfer
Hyunseok Lee, Soheil Abbasloo, Jihoon Tack +1
Reinforcement Learning with Verifiable Rewards (RLVR) has recently strengthened LLM reasoning, but its focus on final answer correctness leaves a critical gap: it does not ensure t…
Vision-aligned Latent Reasoning for Multi-modal Large Language Model
Byungwoo Jeon, Yoonwoo Jeong, Hyunseok Lee +2
Despite recent advancements in Multi-modal Large Language Models (MLLMs) on diverse understanding tasks, these models struggle to solve problems which require extensive multi-step…
ReGUIDE: Data Efficient GUI Grounding via Spatial Reasoning and Search
Hyunseok Lee, Jeonghoon Kim, Beomjun Kim +7
Recent advances in Multimodal Large Language Models (MLLMs) have enabled autonomous agents to interact with computers via Graphical User Interfaces (GUIs), where accurately localiz…
ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim +2
Self-awareness, i.e., the ability to assess and correct one's own generation, is a fundamental aspect of human intelligence, making its replication in large language models (LLMs)…
ReMoDetect: Reward Models Recognize Aligned LLM's Generations
Hyunseok Lee, Jihoon Tack, Jinwoo Shin
The remarkable capabilities and easy accessibility of large language models (LLMs) have significantly increased societal risks (e.g., fake news generation), necessitating the devel…