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Federated Deep Clustering Networks for High-Dimensional and Heterogeneous Data

arXiv:2609.21829v1 Announce Type: cross Abstract: Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized

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Fewer Steps, Better Actions: Rethinking Flow-Matching Inference for VLA Policies

DGX agent

arXiv:2609.21216v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies based on flow matching generate action chunks through repeated evaluations of an action expert. Increasing the n

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21 Sept 2026

FootQuery: Future-Touchdown-Guided Retrieval from Depth History for Perceptive Humanoid Locomotion

arXiv:2609.21447v1 Announce Type: cross Abstract: Humanoid locomotion over complex terrain requires anticipating footholds that may no longer be visible at touchdown. Limited camera coverage and self-

From Pretraining to Proficiency: Real-World Subtask RL for Long-Horizon Manipulation with Minimal Human Intervention

arXiv:2609.21788v1 Announce Type: cross Abstract: A pretrained robot foundation policy may execute most of a long-horizon task yet repeatedly fail at a few critical subtasks. Collecting additional ful

GEM-MPC: Balancing Exploration and Exploitation through Expert-Guided Planning

arXiv:2609.21735v1 Announce Type: new Abstract: Effective exploration in high-dimensional continuous control remains a central challenge in reinforcement learning. Planning-based methods address this

Geometric Mean Pooling for Equal-Weight Multiplicative Coarse-Graining

arXiv:2609.21876v1 Announce Type: new Abstract: As an alternative to the additive and extremal biases of average and max pooling, we introduce Geometric Mean Pooling (GMP), a signed pooling operator t

Goal-Oriented Reactive Simulation for Closed-Loop Trajectory Prediction

arXiv:2603.24155v3 Announce Type: replace Abstract: Current trajectory prediction models are primarily trained in an open-loop manner, which often leads to covariate shift and compounding errors when

GVPO++: Group Variance Policy Optimization for LLM Post-Training and On-Policy Distillation

arXiv:2609.21432v1 Announce Type: new Abstract: Post-training plays a pivotal role in enhancing the reasoning capabilities and task-specific expertise of large language models (LLMs). Despite recent a

HAT: Hypothesis-Anchored Tracking for Video Monocular Spacecraft Pose Estimation

arXiv:2609.21597v1 Announce Type: new Abstract: Monocular 6-DoF pose estimation of non-cooperative targets is important for on-orbit servicing and debris removal. A single-image estimator can confuse

Hiding in Plain Sight: A Diffusion-based Mitigation of Geolocation Privacy Leakage in Vision-Language Models

arXiv:2609.21363v1 Announce Type: new Abstract: Multimodal large reasoning models (MLRMs) have demonstrated remarkable capabilities in complex visual understanding. However, this very power introduces

IncentRL: The Trade-Off Between Preference Guidance and Task Performance

arXiv:2609.21525v1 Announce Type: new Abstract: Preference-based reward shaping can guide reinforcement learning, but adding preference signals to the reward may unintentionally change the task being

Info3R: Information-Adaptive Test-Time Training for 3D Reconstruction

arXiv:2609.21938v1 Announce Type: new Abstract: Transformer-based models have recently achieved strong performance on 3D reconstruction from images, and recent works extend them to process video strea

Information-Gain Rewards over Diversity-Pruned Tests: GT-Anchored Verifier Co-Training for Reliable Code Generation

arXiv:2609.21208v1 Announce Type: new Abstract: Self-play methods that co-train a single language model as both coder and test author promise to move code-generation RL beyond fixed test suites, but t

K2-V2: A 360-Open, Reasoning-Enhanced LLM

arXiv:2512.06201v3 Announce Type: replace Abstract: We introduce K2-V2, a 360-open LLM built from scratch as a superior base for reasoning adaptation, in addition to functions such as conversation and

KnowDemo: Knowledge-Guided Robot Demonstration Generation from Human Videos

arXiv:2609.21229v1 Announce Type: cross Abstract: Learning robot manipulation policies typically requires substantial demonstration data, which are costly to collect on real robots. Recent methods gen

lambda-Controlled GRPO: Turning Flow-Matching Ratio Instability into a Budgeted Resource

arXiv:2609.22041v1 Announce Type: new Abstract: Reinforcement learning is increasingly used to align image generators with reward signals, and Flow-GRPO recently extended this paradigm to flow-matchin

Learning Distance-Conditioned Object Transport for Humanoid Loco-Manipulation from a Single Motion Clip

arXiv:2609.21467v1 Announce Type: new Abstract: Motion tracking can reproduce humanoid loco-manipulation from a single retargeted motion clip, but a policy trained on a fixed reference primarily repro

Learning End-to-End Control for Omnidirectional Aerial Motion on Overactuated Tilt-rotor Quadrotors

arXiv:2602.21583v2 Announce Type: replace Abstract: While reinforcement learning (RL) has been successfully applied to conventional quadrotors for agile and robust flight, whether actuator-level RL ca

Learning Scene-Aware Humanoid Locomotion through 3D Clutter from Immersive Human Demonstrations

arXiv:2609.21107v1 Announce Type: new Abstract: While learning from human motions has enabled highly dynamic humanoid skills such as dancing and martial arts in obstacle-free space, traversal through

M2G-LLM: Enhancing Clinical Prediction via Multimodal Graph Reasoning and LLM Context Injection

arXiv:2609.21164v1 Announce Type: new Abstract: Integrating diverse data modalities --- such as clinical notes, laboratory results, and medical imaging --- is essential for advancing clinical decision

MetaPusher: Meta Learning and Planning for Nonprehensile Manipulation of Unseen Objects with Rapid Online Adaption

arXiv:2609.21122v1 Announce Type: new Abstract: Manipulating previously unseen objects remains challenging, as their dynamics depend on latent physical properties, such as friction and mass distributi

MicroHookACT: Monocular Microscopic Vision Guided Visuomotor Policy for Flexible Microelectrode Hooking

arXiv:2609.21365v1 Announce Type: new Abstract: Automated needle-loop hooking is a critical step in flexible microelectrode (FME) implantation. This paper presents MicroHookACT, an imitation learning-

MintAct: A Unified Visual Agent for Digital Environments

arXiv:2609.22083v1 Announce Type: new Abstract: We present MintAct, a family of vision-language models that unifies UI grounding, multi-step navigation across mobile, desktop, and web, and visual tool

MIST: Multimodal Survival Prediction with Genomic-Guided Histology Attention

arXiv:2609.21811v1 Announce Type: new Abstract: Multimodal survival models can combine complementary prognostic information from whole-slide images and genomic profiles, but effective fusion remains c

Moral Entropy: Auditing Bias and Uncertainty in Moral Judgment

arXiv:2609.21992v1 Announce Type: new Abstract: Most work in computational ethics treats annotator disagreement on moral content as noise to be voted away, collapsed into majority vote or the more per

MT-WAM: Reorienting the One-Pass Predictive Representation Toward Action Generation

arXiv:2609.21474v1 Announce Type: new Abstract: Fast-WAM shows that video-action co-training improves control without generating future video at inference, making the representation from a single vide

NaViRrator: Robot Navigation from Human-Readable Maps through a Learned Visual Route

arXiv:2609.21316v1 Announce Type: new Abstract: Human-readable maps provide an intuitive interface for specifying robot destinations, but connecting their schematic geometry to egocentric observations

On Repulsive and Attractive Teachers: Separating Correctness from Behavior in Self-Distillation

arXiv:2609.21561v1 Announce Type: cross Abstract: On-policy self-distillation provides dense, token-level supervision by conditioning a model on privileged information and distilling the resulting tea

OneBid: A Unified Auto-Bidding Foundation Model for Diverse oCPX Advertising Scenarios

arXiv:2609.21550v1 Announce Type: cross Abstract: Auto-bidding is central to computational advertising, where strategies must maximize advertisers' conversion value under economic constraints. It has

Outcome-Conditioned End-Effector Geometry Across Vision-Language-Action Policies

arXiv:2609.21659v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies solve the same manipulation task through different action interfaces, but task success alone does not establish

Potential-Field Action Representation for Reinforcement Learning in Contact-Rich Manipulation

arXiv:2609.21609v1 Announce Type: cross Abstract: Model-free reinforcement learning can acquire contact-rich robotic manipulation skills through trial-and-error interaction, but it often requires the

Predictable Failure in Multi-Hop Retrieval: Score-Distributional Confidence Scoring and Abstention

arXiv:2609.22056v1 Announce Type: cross Abstract: Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations. We prove two resul

PrismAlign: Prior-Steered Multi-View VLM Alignment for Hallucination-Robust Table OCR

arXiv:2609.21351v1 Announce Type: new Abstract: Table extraction suffers from frequent structural errors and semantic hallucinations. We propose PrismAlign, a multi-VLM framework aligning diverse visu

PSR: Predictive Sensorimotor Representation Learning for Contact-Rich Manipulation

arXiv:2609.21753v1 Announce Type: new Abstract: Contact-rich manipulation requires policies to generate precise actions by reasoning over contact forces, robot configurations, and interaction historie

Rectify, Don't Regret: On-Policy Closed-Loop Training for Multimodal Trajectory Prediction

arXiv:2603.23393v2 Announce Type: replace Abstract: Current trajectory prediction models are primarily trained in an open-loop manner, which often leads to covariate shift and compounding errors when

Recursive Language Models Generalize Out of Domain

arXiv:2609.20831v1 Announce Type: new Abstract: We study when limiting what a language model can see improves learning. We compare standard CoT, the more general learner that reads the full trace, wit

Reinforcement Learning under External Influence: Guarantees, Algorithms, and Sample Complexity

arXiv:2305.16056v5 Announce Type: replace-cross Abstract: In this paper, we study the problem of reinforcement learning under the influence of external events. For this, we consider Markov decision pr

Robust Mixture Models for Algorithmic Fairness Under Latent Heterogeneity

arXiv:2509.17411v2 Announce Type: replace-cross Abstract: Machine learning models optimized for average performance can perform poorly on vulnerable subpopulations. Existing approaches often rely on g

SABER: Learning Attention-based Semantic Affordance for Legged Locomotion

arXiv:2609.21572v1 Announce Type: new Abstract: Perceptive legged locomotion has advanced rapidly by integrating terrain geometry into learned policies, yet the integration of terrain meaning remains

Safe Real-Time Policy Steering via Noise-Space Trajectory Optimization for One-Step Generative Policies

arXiv:2609.21220v1 Announce Type: new Abstract: Generative robot policies can represent diverse, multimodal behaviors, but adapting pretrained policies to deployment-time constraints such as collision

Same World, Different Knowledge: When Isolated Audits Misjudge World-Model Repairs

arXiv:2609.21155v1 Announce Type: new Abstract: A repair favored under an isolated input fault can be inferior when deployed modules share the faulty information. We introduce an information-interface

Scaling Forced Alignment to End-User Devices

arXiv:2609.21145v1 Announce Type: new Abstract: The Viterbi algorithm has been previously used to perform forced alignment of audio to text to mine training data from online resources. However, many e

SeeQ: Training Generalist Value Functions for Long-Horizon Robotic Manipulation

arXiv:2609.22085v1 Announce Type: new Abstract: Despite rapid progress, generalist robot policies remain brittle on complex, long-horizon tasks that comprise multiple stages or require repeated attemp

SpaceDiffusion: Over-the-Orbit Diffusion for Space Generate-and-Forward Communications

arXiv:2609.20899v1 Announce Type: cross Abstract: Satellite communications are an essential component of sixth-generation (6G) mobile networks, which provide ubiquitous connectivity for global service

SteganoBackdoor: Evading Data-Poisoning Defenses via Steganographic Backdoors

arXiv:2511.14301v4 Announce Type: replace-cross Abstract: Transformer-based models are highly susceptible to backdoor attacks via supervised fine-tuning (SFT). To red-team existing data-poisoning defe

Talking Past the Machine: Morality, Politeness, and Alignment in Human-AI Dialogue

arXiv:2609.21401v1 Announce Type: cross Abstract: Conversational AI systems produce fluent, socially appropriate responses, yet whether they participate in cooperative communication or merely simulate

Towards Fine-Grained Object Manipulation: SAM3-Guided Visuomotor Policy with Persistent Memory Learning and Focused Visual Conditioning

arXiv:2609.21621v1 Announce Type: new Abstract: Fine-grained object (FO) manipulation requires robots to distinguish a specified FO from visually similar objects and execute actions reliably despite s

Trajectory Entropy Reinforcement Learning for Robust Robot Motor Skill Learning

arXiv:2505.04193v2 Announce Type: replace Abstract: Simplicity is a critical inductive bias for designing data-driven controllers, especially when robustness is important. Despite the impressive resul