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From the 2 of 18 linked papers with an AI index.

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18 papers

cs.LG2026

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…

cs.CR2026

Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)

Ryozo Masukawa, Ian Bryant, Armita Kazeminajafabadi +6

Autonomous cyber defense systems based on Deep Reinforcement Learning (DRL) have attracted significant research attention, yet remain evaluated almost exclusively against static, h…

cs.AR2026

ExaGEMM: Exploration Framework for CPU-Driven ML Inference via Associative In-Register Computing for Low-Bit GEMM

Hyunwoo Oh, Suyeon Jang, Hanning Chen +3

Low-bit GEMM is increasingly central to efficient ML inference, yet very-low-bit execution remains a poor fit for conventional CPUs. Practical deployment spans fragmented regimes-f…

cs.LG2026

PolyQ: Codesigning End-to-End Quantization Framework for Scalable Edge CPU LLM Inference

Hyunwoo Oh, Suyeon Jang, Hanning Chen +4

PolyQ is a co-designed compiler and quantization framework that assigns per‑channel bit‑widths to LLM activations on CPUs, enabling fine‑grained fractional‑bit precision while keep…

cs.LG2026

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…

cs.LG2026

FusionSense: Tri-Stage Near-Sensor Learning for Runtime-Adaptive Multimodal Edge Intelligence

Sanggeon Yun, Ryozo Masukawa, Minhyoung Na +5

Autonomous systems and smart-industry deployments increasingly split computation across near-sensor, edge, and cloud resources, where tight energy, latency, and reliability budgets…