Papers Continuous Control
“Continuous Control” 태그가 달린 논문 1,432편 · 필터 해제
FBSDiff++: Improved Frequency Band Substitution of Diffusion Features for Efficient and Highly Controllable Text-Driven Image-to-Image Translation
With large-scale text-to-image (T2I) diffusion models achieving significant advancements in open-domain image creation, increasing attention has been focused on their natural extension to the realm of text-driven image-t…
Image-to-Image TranslationContinuous ControlImage ManipulationSelective Steering: Norm-Preserving Control Through Discriminative Layer Selection
Despite significant progress in alignment, large language models (LLMs) remain vulnerable to adversarial attacks that elicit harmful behaviors. Activation steering techniques offer a promising inference-time intervention…
Continuous ControlScalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
Controlling high-dimensional systems in biological and robotic applications is challenging due to expansive state-action spaces, where effective exploration is critical. Commonly used exploration strategies in reinforcem…
Dimensionality ReductionReinforcement LearningContinuous ControlImproving Policy Exploitation in Online Reinforcement Learning with Instant Retrospect Action
Existing value-based online reinforcement learning (RL) algorithms suffer from slow policy exploitation due to ineffective exploration and delayed policy updates. To address these challenges, we propose an algorithm call…
Representation LearningReinforcement LearningContinuous ControlK-Myriad: Jump-starting reinforcement learning with unsupervised parallel agents
Parallelization in Reinforcement Learning is typically employed to speed up the training of a single policy, where multiple workers collect experience from an identical sampling distribution. This common design limits th…
Reinforcement LearningContinuous ControlTwinBrainVLA: Unleashing the Potential of Generalist VLMs for Embodied Tasks via Asymmetric Mixture-of-Transformers
The fundamental premise of Vision-Language-Action (VLA) models is to harness the extensive general capabilities of pre-trained Vision-Language Models (VLMs) for generalized embodied intelligence. However, standard roboti…
Continuous ControlStructure Detection for Contextual Reinforcement Learning
Contextual Reinforcement Learning (CRL) tackles the problem of solving a set of related Contextual Markov Decision Processes (CMDPs) that vary across different context variables. Traditional approaches--independent train…
Reinforcement LearningMulti-Task LearningContinuous ControlTransfer LearningHeterogeneous Multi-Expert Reinforcement Learning for Long-Horizon Multi-Goal Tasks in Autonomous Forklifts
Autonomous mobile manipulation in unstructured warehouses requires a balance between efficient large-scale navigation and high-precision object interaction. Traditional end-to-end learning approaches often struggle to ha…
Reinforcement LearningContinuous ControlSteer Model beyond Assistant: Controlling System Prompt Strength via Contrastive Decoding
Large language models excel at complex instructions yet struggle to deviate from their helpful assistant persona, as post-training instills strong priors that resist conflicting instructions. We introduce system prompt s…
Continuous ControlProjected Autoregression: Autoregressive Language Generation in Continuous State Space
Standard autoregressive language models generate text by repeatedly selecting a discrete next token, coupling prediction with irreversible commitment at every step. We show that token selection is not the only viable aut…
Continuous ControlEnhanced-FQL($λ$), an Efficient and Interpretable RL with novel Fuzzy Eligibility Traces and Segmented Experience Replay
This paper introduces a fuzzy reinforcement learning framework, Enhanced-FQL($λ$), that integrates novel Fuzzified Eligibility Traces (FET) and Segmented Experience Replay (SER) into fuzzy Q-learning with the Fuzzified B…
Reinforcement LearningContinuous ControlCaricatureGS: Exaggerating 3D Gaussian Splatting Faces With Gaussian Curvature
A photorealistic and controllable 3D caricaturization framework for faces is introduced. We start with an intrinsic Gaussian curvature-based surface exaggeration technique, which, when coupled with texture, tends to prod…
Continuous ControlMoments Matter:Stabilizing Policy Optimization using Return Distributions
Deep Reinforcement Learning (RL) agents often learn policies that achieve the same episodic return yet behave very differently, due to a combination of environmental (random transitions, initial conditions, reward noise)…
Reinforcement LearningContinuous ControlEvaluating Feature Dependent Noise in Preference-based Reinforcement Learning
Learning from Preferences in Reinforcement Learning (PbRL) has gained attention recently, as it serves as a natural fit for complicated tasks where the reward function is not easily available. However, preferences often …
Reinforcement LearningContinuous ControlHigher-Order Action Regularization in Deep Reinforcement Learning: From Continuous Control to Building Energy Management
Deep reinforcement learning agents often exhibit erratic, high-frequency control behaviors that hinder real-world deployment due to excessive energy consumption and mechanical wear. We systematically investigate action s…
Reinforcement LearningContinuous ControlContractive Diffusion Policies: Robust Action Diffusion via Contractive Score-Based Sampling with Differential Equations
Diffusion policies have emerged as powerful generative models for offline policy learning, whose sampling process can be rigorously characterized by a score function guiding a stochastic differential equation (SDE). Howe…
Continuous ControlImage GenerationUnified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training
General-purpose robotic systems operating in open-world environments must achieve both broad generalization and high-precision action execution, a combination that remains challenging for existing Vision-Language-Action …
Continuous ControlColaVLA: Leveraging Cognitive Latent Reasoning for Hierarchical Parallel Trajectory Planning in Autonomous Driving
Autonomous driving requires generating safe and reliable trajectories from complex multimodal inputs. Traditional modular pipelines separate perception, prediction, and planning, while recent end-to-end (E2E) systems lea…
Scene UnderstandingTrajectory PlanningContinuous ControlAutonomous DrivingVideos are Sample-Efficient Supervisions: Behavior Cloning from Videos via Latent Representations
Humans can efficiently extract knowledge and learn skills from the videos within only a few trials and errors. However, it poses a big challenge to replicate this learning process for autonomous agents, due to the comple…
Reinforcement LearningContinuous ControlOffline Safe Policy Optimization From Heterogeneous Feedback
Offline Preference-based Reinforcement Learning (PbRL) learns rewards and policies aligned with human preferences without the need for extensive reward engineering and direct interaction with human annotators. However, e…
Reinforcement LearningContinuous Control