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Robust Reinforcement Learning for Dynamic Treatment Regimes under Model and Measurement Uncertainty

arXiv:2610.22336v1 Announce Type: new Abstract: We develop a robust reinforcement learning (RL) framework for learning adaptive treatment policies that generalize across patients and remain reliable u

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Router Drift Control: Mitigating Off-Policy Degradation in Mixture-of-Experts Reinforcement Learning

DGX agent

arXiv:2610.21682v1 Announce Type: cross Abstract: Reinforcement learning (RL) can become off-policy due to training-inference mismatch, mini-batch updates, and asynchronous training.The resulting mism

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16 Oct 2026

Routing Policy Optimization for Online Diffusion Reinforcement Learning

arXiv:2610.22282v1 Announce Type: new Abstract: Reinforcement learning can align visual generators with reward signals beyond their pretraining objectives, but existing score-function methods typicall

Scientific feedback reveals productive regimes beyond training conventions

arXiv:2512.15756v2 Announce Type: replace-cross Abstract: Human-imposed design conventions can restrict the alternatives represented in scientific training data and shape the search preferences learne

Score Mismatch and Set-Constrained Sampling in Zero-Shot Conditional Discrete Diffusion

arXiv:2610.21061v1 Announce Type: cross Abstract: Discrete diffusion models have become a powerful framework for modeling complex discrete distributions across a range of applications. While theoretic

Selection-Safe Conformal Early Exit: Distribution-Free Coverage under Adaptive Depth

arXiv:2610.20773v1 Announce Type: new Abstract: Calibrating a conformal prediction set at each early exit does not preserve coverage once a data-dependent exit is selected. We construct one terminal p

Semantic Alignment of EEG and Text: A Contrastive Learning Framework for Decoding Imagined Speech

arXiv:2610.20766v1 Announce Type: new Abstract: Imagined speech decoding from EEG offers a promising route toward naturalistic brain-computer interfaces. Traditional closed-set classifiers treat seman

ShiftQAT: Quantization-Aware Training for the Numerical Contract of a Fixed-Function Edge CNN Accelerator

arXiv:2610.21695v1 Announce Type: new Abstract: Fixed-function CNN accelerators make edge inference fast and energy-efficient, but they execute only networks that obey a precise numerical contract. On

Skill-Decoupled On-Policy Expert Distillation for Unified Vision-Language Models

arXiv:2610.22217v1 Announce Type: cross Abstract: Reinforcement learning (RL) can elicit specialized visual capabilities in vision-language models (VLMs), yet jointly optimizing heterogeneous objectiv

SOMA: Stack-of-Objects Manipulation using a Quadruped Robot

arXiv:2610.20968v1 Announce Type: cross Abstract: Executing heavy-duty physical manipulation in unpredictable environments remains a major challenge for quadrupedal robots lacking dedicated manipulato

Spatially Conditioned Diffusion Policy: Learning Precise and Robust Manipulation with a Single RGB Camera

arXiv:2606.14535v2 Announce Type: replace Abstract: Recent visual imitation learning systems have widely adopted multi-camera setups with wrist-mounted cameras as the de facto standard. However, manip

Specification Gaming and a Constrained Reinforcement Learning Mitigation in a Cleaning Gridworld

arXiv:2610.22152v1 Announce Type: cross Abstract: Reinforcement learning agents optimize exactly the reward signal they are given, which can diverge sharply from an intended true objective when that s

Spectral-Spatial Interpretation

arXiv:2610.21114v1 Announce Type: cross Abstract: Post-hoc image explanations usually show where a model looks using spatial heatmaps or indicate which channels matter using global channel scores. The

Spectrum Matching: a Unified Perspective for Superior Diffusability in Latent Diffusion

arXiv:2603.14645v2 Announce Type: replace Abstract: In this paper, we study the diffusability (learnability) of variational autoencoders (VAEs) in latent diffusion. We first derive distribution-free b

Spurious Attention Heads in Vision Transformers: Mechanistic Identification of Annotation-Driven Bias in Medical Chest X-Ray Analysis

arXiv:2610.21638v1 Announce Type: cross Abstract: Vision Transformers deployed in medical imaging exploit spurious correlations, yet the internal mechanisms remain unidentified and impossible to fix.

Stochastic Gradient Descent: A Nonlinear Time Series Perspective

arXiv:2610.20894v1 Announce Type: cross Abstract: This paper investigates the statistical behavior of Stochastic Gradient Descent (SGD) with constant step size under the framework of iterated random f

Stop Training Against Soft Users: Mentalized Adversarial Self-Play for Proactive Dialogue

arXiv:2610.21156v1 Announce Type: new Abstract: Proactive dialogue agents must guide multi-turn interactions toward task goals while adapting to users whose intentions and attitudes evolve. Existing p

SUPRA-TEX: 3D Generation with Super-Aligned Texture

arXiv:2610.22352v1 Announce Type: new Abstract: Single image 3D generation aims to dress a given 3D mesh with relightable materials while faithfully preserving the visual details of a reference image.

Terminal-RSI: Recursive Self-Improving Terminal Agents via Recursive Self-Rewrite and Policy-Refine

arXiv:2610.22192v1 Announce Type: new Abstract: Converting verifier outcomes into useful policy updates and partial progress into complete task resolution is crucial for terminal agents. We present Te

The Dormant Spiking Neuron: A State-Driven Mechanism for Efficient Spiking Neural Networks

arXiv:2610.21748v1 Announce Type: new Abstract: Spiking neural networks (SNNs) offer a compelling pathway toward energy-efficient artificial intelligence, fundamentally anchored in presynaptic input-d

The Lagrangian Structure of Cost-Penalized Active Feature Acquisition

arXiv:2610.21919v1 Announce Type: new Abstract: Active Feature Acquisition (AFA) sequentially selects features to maximize predictive accuracy under an acquisition budget. A natural heuristic greedily

Thinking-Free Policy Initialization Makes Distilled Reasoning Models More Effective and Efficient Reasoners

arXiv:2509.26226v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Reward (RLVR) effectively solves complex tasks but demands extremely long context lengths during traini

Thinking with Images as Continuous Actions: Numerical Visual Chain-of-Thought

arXiv:2602.23959v2 Announce Type: replace Abstract: Recent MLLMs increasingly rely on visual chain-of-thought to perform region-grounded reasoning over images. However, existing approaches ground regi

Time to Fake It: Continual Machine Learning Intensifies Unfairness in Deepfake Detection

arXiv:2610.21974v1 Announce Type: cross Abstract: Deepfake detectors safeguard against misinformation, rendering their failures as much a societal as a technical concern. As generators constantly evol

Towards bio-inspired visual navigation: a neuromorphic navigation paradigm for MAVs

arXiv:2610.21978v1 Announce Type: new Abstract: Biological visual navigation achieves remarkable robustness at extremely low power, whereas frame-based robotic systems relying on artificial neural net

Towards Unbiased On-Policy Distillation for Block Diffusion Language Models

arXiv:2610.05373v2 Announce Type: replace Abstract: On-policy distillation (OPD) has emerged as an effective post-training paradigm for language models, with recent efforts extending it to block diffu

TRACE: Typed Reference-Aware Conversational Editing for Humanoid Motion Diffusion

arXiv:2610.21515v1 Announce Type: new Abstract: Language-conditioned humanoid motion generation enables users to create and refine robot movements through natural language. The central challenge is to

Training-Free On-Policy Distillation

arXiv:2610.22236v1 Announce Type: cross Abstract: On-policy distillation consolidates specialist models into one student at the price of rollouts, teacher passes and gradient steps for every teacher.

Transfer Learning in Bandits from Unknown Adaptive Policies: Problem-Dependent Lower and Upper Bounds

arXiv:2610.21582v1 Announce Type: new Abstract: Transfer learning in stochastic multi-armed bandits is typically studied assuming that prior data forms a fixed offline dataset or is generated by a kno

TS-WAM: Temporal Latent Actions and World-Action Coupling for Vision-Language Robot Control

arXiv:2610.21922v1 Announce Type: new Abstract: Many vision-language-action policies rely on action-labeled robot demonstrations and lack an explicit mechanism for predicting future visual states. The

Twice Upon a Time: Complementary Representations for Time-Series Reasoning

arXiv:2610.22327v1 Announce Type: cross Abstract: Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what inf

Uncovering Grounding IDs: How External Cues Shape Multi-Modal Binding

arXiv:2509.24072v5 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) perform well on multimodal tasks, but their ability to reason and precisely align visual and textual info

Uni-PNP: Unified Prehensile and Non-prehensile Policy Learning for Generalizable Object Pose Reaching

arXiv:2610.21735v1 Announce Type: new Abstract: Object manipulation often requires combining non-prehensile actions with grasping. However, existing approaches typically develop these capabilities sep

Value as Memory: Online Value-Guided Post-training for General Robot Policies

arXiv:2610.22368v1 Announce Type: new Abstract: Real-world post-training of generalist robot policies faces two challenges: partial observability makes action selection ambiguous, while offline post-t

Value-Informed Schedule Trimming for Accelerated Sequential Monte Carlo Guidance in Discrete Diffusion

arXiv:2610.20669v1 Announce Type: new Abstract: Reward-guided discrete diffusion enables test-time alignment with downstream objectives, but applying Sequential Monte Carlo (SMC) guidance at every den

Velox: Spatial Memory Makes World Models Efficient

arXiv:2610.22311v1 Announce Type: new Abstract: Video world models turn actions and camera motion into long visual rollouts, making video a natural interface for interactive simulation. Such interacti

VeriVLA: Adaptive Test-Time Verification for Flow-Based VLAs with Latent World Models

arXiv:2610.21985v1 Announce Type: new Abstract: Flow-based Vision-Language-Action (VLA) policies are inherently stochastic: different noise seeds can produce action chunks of varying quality from the

Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation

arXiv:2610.21601v1 Announce Type: cross Abstract: Policy-shift distillation reuses the difference between a teacher's log probabilities before and after reinforcement learning (RL) as supervision on s

What Should Robot Policies Learn to Predict? Rethinking Supervision Targets in Vision-Language-Action Learning

arXiv:2610.21915v1 Announce Type: new Abstract: Vision-language-action (VLA) policies are typically trained with action prediction as the primary supervision signal, since robots ultimately execute ac

When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles

arXiv:2610.21139v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used upstream of decision-making to clean data, detect label errors, and reconstruct missing values. Yet

When to Ask for Help: A Decision-Theoretic Account and Measurement Standard for Slow-Module Scheduling in Dual-System Vision-Language-Action Models

arXiv:2610.21160v1 Announce Type: new Abstract: Dual-system vision-language-action (VLA) models pair a high-frequency fast policy with a slow, expensive module, and published trigger mechanisms for in

Where, How, and When: Query-Guided Grounding for Video Understanding

arXiv:2610.21422v1 Announce Type: cross Abstract: Understanding video content requires reasoning at multiple levels of granularity, from identifying objects to interpreting their interactions and loca

Where to Steer: Input-Dependent Layer Selection for Steering Improves LLM Alignment

arXiv:2604.03867v2 Announce Type: replace Abstract: Steering vectors have emerged as a lightweight and effective approach for aligning large language models (LLMs) at inference time, enabling modulati

Whole-Body Dexterity

arXiv:2610.22184v1 Announce Type: cross Abstract: Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans' ability to engage the en

Why Shallow Neural Networks Learn Sinusoidal Components First: An Orthogonal Polynomial Dynamics Framework

arXiv:2610.21964v1 Announce Type: cross Abstract: Neural networks often learn low-frequency components before high-frequency ones --- a phenomenon called spectral bias or termed F-principle. Many nume

X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation

arXiv:2610.21450v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chu

A Large-Dimensional Analysis of Least-Squares Federated Learning via Generalized Total Variation Minimization

arXiv:2610.20075v1 Announce Type: new Abstract: Federated learning over decentralized networks inherently trades off the suppression of local finite-sample noise through collaboration against the bias

15 Oct 2026

A^3PreCore: Robust Rigid Registration for Native FLAIR-Space Brain-Mask Transfer

arXiv:2610.20561v1 Announce Type: new Abstract: Reliable brain-mask transfer into native fluid-attenuated inversion recovery (FLAIR) space can fail when T1-to-FLAIR rigid registration is unstable. We