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Equivariant Neural Primal-Dual Assignment for Maximum Common Edge Subgraphs

arXiv:2609.32661v1 Announce Type: new Abstract: Maximum common edge subgraph (MCES) matching finds a partial vertex correspondence between two labeled graphs that preserves as many labeled edges as po

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Estimate, Don't Imitate: Reusing Differentiable State-Based Policies for Visuomotor Control

DGX agent

arXiv:2609.34018v1 Announce Type: cross Abstract: Simulation-trained manipulation policies can exploit privileged state information to learn effective contact-rich behaviours, but deployment requires

safetyarxiv-cs-lg

29 Sept 2026

eVGGT: An Efficient Geometry-Aware Vision Encoder for Visuomotor Policies

arXiv:2509.15880v2 Announce Type: replace Abstract: Geometry-grounded vision models, such as VGGT, have emerged as robust visual encoders, providing essential geometric priors for robotic manipulation

Evidence-Aligned Multimodal On-Policy Self-Distillation for Fine-Grained Visual Understanding

arXiv:2609.34672v1 Announce Type: new Abstract: Fine-grained visual understanding requires models to recognize small details within complex images. Multimodal on-policy self-distillation (OPSD) addres

Evolution of fairness in multi-objective reinforcement learning framework

arXiv:2609.34114v1 Announce Type: new Abstract: Fairness, as a fundamental social norm, continues to pose a longstanding puzzle regarding its emergence. Traditional game-theoretic models largely rely

ExpertoRhythm: Morphology-Aware Learning for Waveform Reconstruction and Cuffless Blood Pressure Estimation from Single-Channel PPG

arXiv:2609.34146v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring from photoplethysmography (PPG) has strong potential for wearable health and telemonitoring, but accu

F4R: Failure-Driven Recognition, Reconstruction, Refinement, and Redeployment for Continual Robot Self-Improvement

arXiv:2609.35575v1 Announce Type: new Abstract: The real-world performance of current vision-language-action models is fundamentally constrained by the limited coverage of expert demonstrations and th

FailPatch: Failure Residual Patching for Vision-Language-Action Models

arXiv:2609.34175v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are typically adapted using successful demonstrations, which provide direct action supervision but rarely cover fa

FARE: Deep Reinforcement Learning For Fair Exposure Constrained Uncertainty Aware Financial Content Personalization

arXiv:2609.31890v1 Announce Type: new Abstract: Content personalization systems in financial services must ensure fair exposure across diverse offerings-a requirement driven by contractual obligations

Feedback-Robust AI for Patient Knowledge Graphs

arXiv:2609.33248v1 Announce Type: new Abstract: Patient knowledge graphs from bedside monitoring should type their relations and state whether the data support their signs. In anesthesia and intensive

FestDPO: Few-step Generator Alignment with Direct Preference Optimization

arXiv:2609.34673v1 Announce Type: new Abstract: Few-step generative models can generate high-fidelity samples within a few function evaluations. Despite this efficiency, generated samples may not exhi

Fewer Tokens, More Self-Teaching: On-Policy Self-Distillation for Extreme Visual Token Reduction

arXiv:2609.32353v1 Announce Type: new Abstract: Visual token reduction is an effective way to accelerate multimodal large language models (MLLMs), but performance deteriorates rapidly under extremely

Find Something You Can't Do: Agentic Real-World Reinforcement Learning for Self-Improving VLA Models

arXiv:2609.32069v1 Announce Type: new Abstract: Vision--language--action (VLA) models provide strong priors for robotic manipulation but are typically deployed as frozen policies, unable to improve fr

FINGR: Learning Dexterous Hand Control for Real-World Rubik's Cube Solving

arXiv:2609.33973v1 Announce Type: new Abstract: Manipulating a Rubik's Cube with a single dexterous hand is a challenging test of sustained, contact-rich control: the hand must execute successive laye

Finite-Time Concentration and Convergence Rates for Projected Two-Time-Scale Stochastic Approximation with Markov Noise

arXiv:2609.34791v1 Announce Type: cross Abstract: We study finite-time concentration and convergence rates for projected two-time-scale stochastic approximation driven by a controlled Markov chain. Th

First Learn, Then Memorize: The Spectral Bias of Diffusion Models

arXiv:2609.35377v1 Announce Type: new Abstract: Diffusion models trained on a finite dataset first learn to generate novel, high-quality samples and only much later collapse onto their training set. W

Fisher-Informed Recalibration for Feedback-Based On-Policy Self-Distillation of LLMs

arXiv:2609.34009v1 Announce Type: new Abstract: Feedback-based on-policy self-distillation has emerged as a promising approach for enabling foundation models, more specifically Large Language Models (

FlexiWorld: Learning and Planning via Flexible Action Chunks Across Multiple Time Scales

arXiv:2609.35138v1 Announce Type: new Abstract: Latent world models predict future states for goal-directed planning using action chunks spanning multiple primitive steps. Existing methods typically u

FlexLoop: Depth-Elastic Looped Policies for Adaptive Test-Time Computation in Deep RL

arXiv:2609.34488v1 Announce Type: new Abstract: Looped architectures scale computation by reusing the same parameters across recurrent steps, and recent work shows that they substantially improve deep

Flow-Matching-Based Protein Structure Tokenizer Made Efficient and Easy

arXiv:2609.33129v1 Announce Type: new Abstract: As the bridge between protein modality and discrete modeling, protein structure tokenization still largely relies on heavily engineered training objecti

Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals

arXiv:2609.32773v1 Announce Type: cross Abstract: Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured for

Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment

arXiv:2602.00974v2 Announce Type: replace Abstract: Label-supervised manifold alignment bridges the gap between unsupervised and correspondence-based paradigms by leveraging shared label information t

FoundDSR: A Generalizable Foundation Model with Guided 2D Gaussian Splatting for Depth Super-Resolution

arXiv:2609.32323v1 Announce Type: new Abstract: We introduce FoundDSR, a generalizable foundation model for robust depth reconstruction across unseen data distributions using RGB-D pairs. FoundDSR beg

From Dual Tracking to Clipping: Provably Faster Distributionally Robust Multi-Objective Optimization

arXiv:2605.05660v2 Announce Type: replace Abstract: Multi-objective optimization (MOO) has received growing attention in applications that require learning under multiple criteria. However, most exist

From Pixel to Poses: Object-centric Tool Manipulation Learning from Human Demonstrations

arXiv:2609.35375v1 Announce Type: new Abstract: Scaling up robotic manipulation is primarily bottlenecked by the scarcity of real-world robot data. While recent approaches leverage human video demonst

From Scores to Samples: Elastic Forcing for Autoregressive Video Generation

arXiv:2609.35491v1 Announce Type: new Abstract: Few-step autoregressive video generation commonly relies on Distribution Matching Distillation (DMD), requiring a bidirectional diffusion teacher and an

From Static to Dynamic: On-Policy Distillation from Image to Video Diffusion Models

arXiv:2609.34371v1 Announce Type: new Abstract: On-policy distillation (OPD) specializes pretrained video diffusion models through teacher supervision along the student's own generation trajectory. Al

From World Models to World Action Models: Rethinking Next-State Prediction

arXiv:2609.34414v1 Announce Type: new Abstract: Predicting the next state is a core paradigm of World Models for modeling physical dynamics, emphasizing prediction fidelity. As World Models evolve int

Frontier Learning: Training LLM Reasoners at the Edge of Capability

arXiv:2609.35426v1 Announce Type: new Abstract: Reinforcement Learning-based post-training of Large Language Models (LLM) has been successfully applied to improve their reasoning capabilities. Existin

Functional Autoencoders for Amplitude-Phase Representation Learning

arXiv:2609.34207v1 Announce Type: cross Abstract: Functional data are intrinsically infinite-dimensional, and often exhibit phase variation, where corresponding events occur at different times across

Future Information-Directed Sampling for Bayesian Nonstationary Bandits

arXiv:2609.33981v1 Announce Type: new Abstract: Exploration--exploitation is a central trade-off in bandit learning. While classical algorithms such as upper confidence bound methods and Thompson Samp

Fysiverse-3D-SimReady Technical Report: Agentic Physical Simulation for Pragmatic 3D World Reconstruction

arXiv:2609.31715v1 Announce Type: new Abstract: Agentic recognition requires visual perception to move beyond static scene understanding and produce structured scene representations that support the p

G^3-LoRA: Organizing Reward-Weighted Video Data with Gradient-Guided Grouped LoRA

arXiv:2609.35189v1 Announce Type: new Abstract: Post-training foundation video models on heterogeneous reward-weighted data usually assume that all data categories induce compatible updates. This assu

GAE: General Action Expert for Real-Time Humanoid Teleoperation

arXiv:2609.34233v1 Announce Type: new Abstract: Humanoid avatars extend human physical presence beyond the body, enabling people to participate in social, service, and labor activities through remotel

GAUGE: Group-Wise View-Inconsistency Rectification for Feed-Forward 4D Tracking

arXiv:2609.32596v1 Announce Type: new Abstract: Feed-forward models regress dense 3D point trajectories directly from monocular video, yet the residual after global alignment is substantial and lacks

Gaze Prompts: Temporally Dense Human Attention for Vision-Language-Action Fine-Tuning

arXiv:2609.34550v1 Announce Type: new Abstract: Vision-Language-Action (VLA) fine-tuning pairs images with actions at every step, yet typically provides only a task-level language instruction, leaving

Geometry-Preserving Blind Watermarking for Raw 3D Point Clouds

arXiv:2609.32222v1 Announce Type: new Abstract: Raw 3D point clouds are a core geometric representation. Establishing their ownership is challenging because point sets are irregular, unstructured, and

Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts

arXiv:2609.32788v1 Announce Type: new Abstract: Deep learning has transformed symbolic music generation by borrowing the training paradigms of large language models, with systems such as NotaGen now p

GLF-Q: Global-Local Feature-based Quantization for Vision Transformers

arXiv:2609.34564v1 Announce Type: new Abstract: Post-training quantization (PTQ) efficiently compresses Vision Transformers (ViTs) without retraining, yet suffers severe accuracy degradation at low bi

Graph Forward Distribution Matching for Molecular Inverse Design

arXiv:2609.32056v1 Announce Type: new Abstract: Achieving precise control over multiple properties without sacrificing chemical validity remains a central challenge in molecular inverse design. Existi

Graph World Models for Constrained Epidemic Policy Planning

arXiv:2609.35545v1 Announce Type: new Abstract: Epidemic policy planning often requires coordination between geographical regions, taking into account mobility-driven spillovers and how to make use of

GraphHCA: Closed-Form Hindsight Credit Assignment for Long-Horizon LLM Agents

arXiv:2609.35084v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has advanced large language models (LLMs) and is increasingly extending to agentic tasks, where sparse terminal

Grasp2Twist: Learning Bimanual Dexterous Jar Opening by Reinforcement Learning

arXiv:2609.32064v1 Announce Type: new Abstract: This paper presents Grasp2Twist, a bimanual dexterous manipulation system that learns to grasp and twist open jar lids using reinforcement learning. Lea

Groupwise Agentic Grading and Advantage Redistribution for Code Agent RL

arXiv:2609.32577v1 Announce Type: cross Abstract: Reinforcement learning (RL) for code agents often uses executable tests to provide binary rewards. With these rewards, Group Relative Policy Optimizat

GT-VLA: Target-Conditioned Trace Guidance for Generalizable Robotic Manipulation

arXiv:2609.31904v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong performance on robotic manipulation, but they often struggle to generalize to unseen tasks, conf

HapticWorld: an Interactive World Simulator with Real-time Torque Feedback

arXiv:2609.31924v1 Announce Type: new Abstract: Contact-rich manipulation depends on force sensing that is hard to infer from visual signals alone, both for collecting demonstrations and for training

Hardware-Aware Features for CUTLASS Kernel Selection

arXiv:2609.35587v1 Announce Type: new Abstract: GPU libraries such as CUTLASS expose tens of thousands of semantically equivalent kernels for a single operation, making exhaustive autotuning expensive

Helical Tendon-Driven Continuum Robot with Programmable Follow-the-Leader Operation

arXiv:2601.13177v2 Announce Type: replace Abstract: Spinal cord stimulation (SCS) is widely used for pain management and has recently shown promise in promoting functional recovery following spinal co