5 papers
Vector Symbolic Policy Gradient
Ryozo Masukawa, Sanggeon Yun, SungHeon Jeong +6
We answer this question with Vector-Symbolic Policy Gradient (VSPG), a discrete-action actor that represents each action by a unit-norm hypervector and scores it by similarity to t…
Qubit-Efficient Quantum Search for Hyperdimensional Decomposition via Logarithmic Encoding
Sanggeon Yun, Hyunwoo Oh, Ryozo Masukawa +2
Hyperdimensional Computing (HDC) represents symbols using high-dimensional hypervectors of dimension . In hypervector decomposition, the objective is to recover constituent…
MissionHD: Hyperdimensional Refinement of Distribution-Deficient Reasoning Graphs for Video Anomaly Detection
Sanggeon Yun, Raheeb Hassan, Ryozo Masukawa +2
LLM-generated reasoning graphs, referred to as mission-specific graphs (MSGs), are increasingly used for video anomaly detection (VAD) and recognition (VAR). However, they are typi…
-Musketeers: Reinforcement Learning Shapes Collaboration Among Language Models
Ryozo Masukawa, Sanggeon Yun, Hyunwoo Oh +8
Recent progress in reinforcement learning with verifiable rewards (RLVR) shows that small, specialized language models (SLMs) can exhibit structured reasoning without relying on la…
HopFormer: Sparse Graph Transformers with Explicit Receptive Field Control
Sanggeon Yun, Raheeb Hassan, Ryozo Masukawa +2
Graph Transformers typically rely on explicit positional or structural encodings and dense global attention to incorporate graph topology. In this work, we show that neither is ess…