9 papers
Compositional Average Velocity Modeling for Efficient Diffusion Offline Reinforcement Learning
Thanh Nguyen, Abu Hanif Muhammad Syarubany, Hwanhee Kim +1
Diffusion-based policies have recently emerged as a powerful paradigm for offline reinforcement learning, but their reliance on multi-step denoising introduces substantial computat…
Locomotion-Grounded Humanoid Soccer: Task-Gated Reinforcement Learning of a Multi-Directional Kicking Library
Abu Hanif Muhammad Syarubany, Jaehyun Jang, Hwanhee Kim +3
Recent humanoid soccer systems make motion tracking the substrate and derive locomotion from it, typically by steering a motion-reference anchor toward the ball. This yields strong…
Event-Driven Refresh and Recurrence Memory to Reduce Stale Grounding in Referring Video Object Segmentation
Abu Hanif Muhammad Syarubany, Jaehyun Jang, Siwoo Lim +2
Referring Video Object Segmentation (RVOS) aims to produce a pixel-accurate mask sequence for an object specified by natural language. Sa2VA combines a multimodal large language mo…
EquivDP3: A SIM(3)-Invariant Point-Cloud Encoder for Data-Efficient Humanoid Loco-Manipulation
Abu Hanif Muhammad Syarubany, Chang D. Yoo
Visuomotor policies for humanoid loco-manipulation must generalize across object poses and lighting from only a handful of demonstrations. 3D Diffusion Policy (DP3) conditions a di…
LLM-Based Agentic Exploration for Robot Navigation & Manipulation with Skill Orchestration
Abu Hanif Muhammad Syarubany, Farhan Zaki Rahmani, Trio Widianto
This paper presents an end-to-end LLM-based agentic exploration system for an indoor shopping task, evaluated in both Gazebo simulation and a corresponding real-world corridor layo…
Diffusion Posterior Sampling for Super-Resolution under Gaussian Measurement Noise
Abu Hanif Muhammad Syarubany
This report studies diffusion posterior sampling (DPS) for single-image super-resolution (SISR) under a known degradation model. We implement a likelihood-guided sampling procedure…
Adversarial and Score-Based CT Denoising: CycleGAN vs Noise2Score
Abu Hanif Muhammad Syarubany
We study CT image denoising in the unpaired and self-supervised regimes by evaluating two strong, training-data-efficient paradigms: a CycleGAN-based residual translator and a Nois…
Vehicle Classification under Extreme Imbalance: A Comparative Study of Ensemble Learning and CNNs
Abu Hanif Muhammad Syarubany
Accurate vehicle type recognition underpins intelligent transportation and logistics, but severe class imbalance in public datasets suppresses performance on rare categories. We cu…
PentaRAG: Large-Scale Intelligent Knowledge Retrieval for Enterprise LLM Applications
Abu Hanif Muhammad Syarubany, Chang Dong Yoo
Enterprise deployments of large-language model (LLM) demand continuously changing document collections with sub-second latency and predictable GPU cost requirements that classical…