Papers Continuous Control
“Continuous Control” 태그가 달린 논문 1,431편 · 필터 해제
Controllable Affective Generation via Latent Vector Steering
Large Language Models (LLMs) often produce emotionally flattened responses after alignment, limiting their effectiveness in affect-sensitive applications. In this paper, we propose EmoVec, a lightweight framework for con…
Continuous ControlGraph-Operator World Models for Morphology-Parameter Generalization in Continuous Control
World models for continuous control are commonly trained for a fixed physical system and can degrade when known morphology parameters such as link lengths, masses, damping, and actuation change. Existing approaches often…
Continuous ControlOrthogonal JEPA: Factorized Predictive States for Latent World Models
World models construct latent states that support prediction, planning, and reasoning about an underlying system. Joint-embedding predictive architectures (JEPAs) offer a direct way to learn such states by predicting tar…
Continuous ControlTo Go Far, Go Together: Diverse Preferences Induce a Curriculum for Reward Optimization
Learning a reward model from human feedback and optimizing a policy against it is one approach to aligning AI systems with individual users. From a fairness perspective, existing work improves such alignment by developin…
Continuous ControlAn Omitted Mode Is a Rare Rule: The Sampling-Verification Danger Law in Continuous Code World Models
In the Code World Model paradigm an LLM synthesizes an executable world model that a classical planner searches, and the model is accepted when it reproduces sampled transitions. We ask what that acceptance certifies in …
Continuous ControlObservation-Grounded Self-Predictive Reinforcement Learning for Visual Continuous Control
Sample-efficient policy learning from pixels is a long-standing challenge in reinforcement learning (RL). Recent dynamics-based representation learning methods have significantly improved the sample efficiency of model-f…
Representation LearningReinforcement LearningContinuous ControlFreqNav: Stage-Wise Frequency Routing for Object-Oriented Aerial Vision-Language Navigation
Object-oriented aerial vision-and-language navigation (VLN) requires searching for a described target and landing on it precisely, under long-horizon and closed-loop control. Guided by a target-descriptive instruction du…
Vision-Language NavigationContinuous ControlGeometry-guided Emotion Modulation for Controllable and Photorealistic Emotional Talking Face Generation
Audio-driven emotional talking face generation aims to synthesize realistic videos with expressive facial dynamics. However, existing methods struggle to balance controllability and visual fidelity. Although implicit rep…
Talking Face GenerationContinuous ControlCollaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning
Deep off-policy reinforcement learning algorithms for continuous control typically rely on neural value function approximation to guide policy improvement. However, temporal-difference (TD) learning introduces noisy targ…
Reinforcement LearningContinuous ControlShared Voxel-Map-Based Cooperative Indoor UAV Guidance with a Multi-Agent Soft Actor-Critic Controller
This paper presents a cooperative indoor UAV guidance framework that combines a shared voxel-map world model with a multi-agent Soft Actor-Critic (MASAC) controller. Multiple drones fuse 360 LiDAR observations into a com…
Continuous ControlHierarchical Soft Actor-Critic for Sparse-Reward Long-Horizon Reinforcement Learning
Exploration in sparse-reward long-horizon tasks poses significant challenges for reinforcement learning. To address these challenges, we propose a two-level Hierarchical Reinforcement Learning (HRL) framework. The first …
Hierarchical Reinforcement LearningContinuous ControlKoopman Dreamer: Spectrally Constrained Latent Dynamics for Stable World-Model Imagination
Latent world models improve sample efficiency in continuous control by optimizing policies over imagined latent trajectories, but common neural transitions offer limited direct control over modal persistence and error ac…
Continuous ControlSMC-ES: Automated synthesis of formally verified control policies
The deployment of autonomous cyber-physical systems in safety-critical environments requires closed-loop control strategies (i.e., policies) that are not only performant but also provably safe and robust. While learning-…
Reinforcement LearningContinuous ControlReflex: Real-Time VLA Control through Streaming Inference
Flow matching Vision-Language-Action (VLA) models promise precise continuous control, but their iterative denoising nature introduces fundamental incompatibilities with real-time robotics: global timestep injection inval…
Continuous ControlLatent Memory Palace: Reasoning for Control as Autoregressive Variational Inference
Human decision-making is highly flexible -- some actions are taken immediately; others require longer deliberation. Language models have exhibited a similar capacity for adaptive "reasoning." However, transferring this c…
Reinforcement LearningContinuous ControlCURE: Controllable Unified Image Restoration for Complex Degradations
The presence of composite degradations poses a significant challenge, since the underlying corruption factors exhibit complex and interdependent interactions. Even when the degradation types are known, accurately restori…
Unified Image RestorationContinuous ControlRank-Then-Act: Reward-Free Control from Frame-Order Progress
We introduce Rank-Then-Act (RTA), a framework for learning control policies from expert video demonstrations without environment rewards. RTA trains a Vision-Language Model (VLM) offline as a progress-based ordinal score…
Reinforcement LearningContinuous ControlLanguage-Critique Imitation Learning from Suboptimal Demonstrations
Prior work on imitation learning from suboptimal demonstrations typically relies on compressed supervision signals such as confidence estimates, discriminator scores, or importance weights. These scalar signals are inher…
Reinforcement LearningContinuous ControlZ-1: Efficient Reinforcement Learning for Vision-Language-Action Models
Vision-Language-Action (VLA) models offer a promising framework for robotic manipulation by connecting language instructions, visual observations, and continuous control. However, most existing policies remain limited by…
Reinforcement LearningContinuous ControlSpikeVLA: Vision-Language-Action Models with Spiking Neural Networks
Vision-Language-Action (VLA) models have become a dominant paradigm for embodied intelligence. However, most existing approaches are built on large-scale transformers, resulting in substantial inference latency and energ…
Representation LearningContinuous Control