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arXiv:2204.08476v2 Announce Type: replace-cross Abstract: In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased

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Residual-Conservative Model Predictive Path Integral Control

DGX agent

arXiv:2607.06950v1 Announce Type: cross Abstract: Sampling-based model predictive control methods handle nonlinear dynamics and complex cost landscapes through Monte Carlo rollouts, yet typically empl

safetyarxiv-cs-ro

9 Jul 2026

Restricted Dynamic Geometric Complexity: Certificates for Structured Preconditioning

model-releasesarxiv-cs-lg

arXiv:2607.07204v1 Announce Type: cross Abstract: Optimization geometrodynamics views optimizer state as evolving geometry. Its full positive-definite quadratic benchmark gives the least affine-invari

Rethinking Multimodal Time-Series Forecasting Evaluation

model-releasesarxiv-cs-lg

arXiv:2607.06973v1 Announce Type: new Abstract: We introduce a new context-enriched, multimodal time series forecasting benchmark, TimesX. TimesX contains a wide selection of high-quality real-world t

Retrieving and Refining Winning Noise Tickets for Diffusion-Based Motion Generation

model-releasesarxiv-cs-cv

arXiv:2607.06843v1 Announce Type: new Abstract: Diffusion-based text-to-motion models synthesize realistic human motions but often exhibit semantic drift from the input text. Motion is inherently temp

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26

arXiv:2607.07498v1 Announce Type: cross Abstract: Testing is a major effort for the gaming industry, requiring a significant part of development budget and people power. We present a case study on a d

applicationsarxiv-cs-ai

Reward Valuation in Vision Language Models: Causal Mechanisms Underlying Anhedonia

arXiv:2607.06626v1 Announce Type: new Abstract: Recent Vision-Language Models capture increasingly complex aspects of human cognition. Here we ask whether this alignment extends to reward valuation, w

local-aiarxiv-cs-lg

Riemannian Geometry for Pre-trained Language Model Embeddings

arXiv:2607.07047v1 Announce Type: cross Abstract: Understanding the geometric structure of pre-trained language model embeddings matters for interpretability and safety. We ask whether sentence-level

RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning

arXiv:2601.00086v3 Announce Type: replace Abstract: Large language models (LLMs) often struggle to use tools reliably in domain-specific settings, where APIs may be idiosyncratic, under-documented, or

agentsarxiv-cs-cl

RL Post-Training Builds Compositional Reasoning Strategies

arXiv:2607.07646v1 Announce Type: new Abstract: Does RL post-training merely amplify primitive skills already latent in a base model, or can it compose primitive skills into new higher-level strategie

RLVP: Penalize the Path, Reward the Outcome

arXiv:2607.07435v1 Announce Type: cross Abstract: Agents acting on our behalf in the real world (e.g. placing phone calls) must learn online from costly, often irreversible interactions rather than ch

ROAD-Waymo: A Large-Scale Action Awareness Dataset for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2411.01683v3 Announce Type: replace Abstract: Autonomous Vehicle (AV) perception systems require more than simply seeing, via e.g., object detection or scene segmentation. They need a holistic u

RoboLight: A Dataset with Linearly Composable Illumination for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2603.04249v2 Announce Type: replace Abstract: In this paper, we introduce RoboLight, the first real-world robotic manipulation dataset capturing synchronized episodes under systematically varied

RoboSnap: One-Shot Real-to-Sim Scene Generation for Generalizable Robot Learning and Evaluation

arXiv:2607.06699v1 Announce Type: new Abstract: Recovering real-world scenes as interactive simulation environments can enable generalizable robot learning and reproducible policy evaluation. However,

safetyarxiv-cs-ro

Robust Federated Learning Under Real-World Client Churn

arXiv:2607.06979v1 Announce Type: new Abstract: Federated Learning (FL) enables training shared models on private, on-device data, but production deployments remain constrained to slow, multi-day refr

local-aiarxiv-cs-lg

Robust Human-AI Complementarity under Uncertainty

arXiv:2607.06656v1 Announce Type: new Abstract: Machine learning models are often intended to augment rather than replace human decision makers, by providing information that is complementary to human

applicationsarxiv-cs-lg

Safe Reinforcement Learning using Ideas from Model Predictive Control

arXiv:2607.07252v1 Announce Type: new Abstract: Reinforcement learning (RL) enables the synthesis of control policies directly from data, making it highly appealing for complex cyber-physical systems

safetyarxiv-cs-lg

Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence

arXiv:2607.07675v1 Announce Type: new Abstract: Despite the recent promise in robot control, video generative models suffer from a domain mismatch due to their primary focus on content creation. For e

safetyarxiv-cs-cv

Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation

arXiv:2603.00233v2 Announce Type: replace-cross Abstract: Quantum generative modeling is a rapidly evolving discipline at the intersection of quantum computing and machine learning. Contemporary quant

Search, Fail, Recover: A Training Framework for Correction-Aware Reasoning

arXiv:2607.07492v1 Announce Type: new Abstract: Many reasoning tasks are not well described by a single left-to-right chain: a solver may need to pursue a plausible branch, observe delayed failure, an

Security and Privacy in Agentic AI: Grand Challenges and Future Directions

arXiv:2607.06608v1 Announce Type: cross Abstract: We present key challenges and future research directions in the security and privacy of agentic AI, based on a horizon-scanning exercise that brought

Seeing What Matters: Lesion-Aware High-Resolution Patch Discovery and Fusion for Chest X-ray Report Generation

arXiv:2607.06909v1 Announce Type: new Abstract: Despite rapid advances in chest X-ray (CXR) foundation models, most radiology report generation (RRG) systems still rely on heavily downsampled inputs (

Segmenting Low-Contrast XCTs of Concrete: An Unsupervised Approach

arXiv:2603.00127v2 Announce Type: replace Abstract: X-Ray Computed Tomography (XCT) is a compelling tool in experimental mechanics, capable of non-destructively extracting information pertaining to th

local-aiarxiv-cs-cv

Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF

arXiv:2607.07693v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) has emerged as a powerful paradigm for aligning generative models with human preferences. However, a

Self-Supervised Pretraining Improves Cross-Site and Cross-Scale Robustness of Point Cloud Leaf-Wood Segmentation

arXiv:2607.06948v1 Announce Type: cross Abstract: The accuracy of existing leaf-wood segmentation methods for tree point clouds varies across forest types and sites. Self-supervised learning (SSL) on

Shared Modular Recurrence in Contextual MDPs for Universal Morphology Control

arXiv:2506.08630v3 Announce Type: replace Abstract: A universal controller for any robot morphology would greatly improve computational and data efficiency. Steps have been made towards such multi-rob

SHTA: Semantic Hard Token Correction and Center Alignment for Semi-Supervised Medical Image Segmentation

arXiv:2607.07019v1 Announce Type: new Abstract: Recent advances in semi-supervised medical image segmentation have achieved remarkable performance through prediction consistency, pseudo-label supervis

safetyarxiv-cs-cv

Siamese Neural Network for Label-Efficient Critical Phenomena Prediction in 3D Percolation Models

model-releasesarxiv-cs-lg

arXiv:2507.14159v2 Announce Type: replace-cross Abstract: Predicting critical phenomena from limited labeled data remains a challenging task in statistical physics. As percolation theory provides a ca

Simulstream: Open-Source Toolkit for Evaluation and Demonstration of Streaming Speech-to-Text Translation Systems

arXiv:2512.17648v2 Announce Type: replace Abstract: Streaming Speech-to-Text Translation (StreamST) requires producing translations concurrently with incoming speech under strict latency constraints,

researcharxiv-cs-cl

Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning

arXiv:2607.07508v1 Announce Type: cross Abstract: Reinforcement learning (RL) is becoming increasingly important for post-training large language models (LLMs). Previous RL pipelines for LLMs were mos

SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents

arXiv:2607.07676v1 Announce Type: new Abstract: Autonomous AI agents can execute complex tasks with limited human review, yet they often lack the grounded operational knowledge to make their outputs n

Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware

arXiv:2607.06915v1 Announce Type: new Abstract: Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising fo

local-aiarxiv-cs-cv

SmartHomeSecure: Automated Detection and Repair of Smart Home Configuration Errors Using Large Language Models

arXiv:2607.06748v1 Announce Type: cross Abstract: Smart home automation platforms increasingly rely on user-authored YAML configuration files to define device behaviors, but these files are prone to s

Tutorials

Smooth Operator: A Real-Time Sampling-Based Algorithm for Kinematic Hand Retargeting

arXiv:2607.07491v1 Announce Type: new Abstract: Advances in learning-based robotic manipulation, such as Vision-Language-Action (VLA) models and Video Action Models (VAMs), heavily rely on high-qualit

tutorialsarxiv-cs-ro

SoccerNet 2026 Challenges Results

arXiv:2607.07320v1 Announce Type: new Abstract: The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision rese

applicationsarxiv-cs-cv

SOMtime the World Ain't Fair: Violating Fairness Using Self-Organizing Maps

arXiv:2602.18201v2 Announce Type: replace Abstract: Unsupervised representations are widely assumed to be neutral with respect to sensitive attributes when those attributes are withheld from training.

SonoRank: Towards Calibration-Free Real-Time Finger Flexion Detection from Forearm Ultrasound Sequences

arXiv:2607.07542v1 Announce Type: cross Abstract: Powered prosthetic hands are frequently abandoned, largely due to the limited functionality of current devices that rely on surface electromyography (

SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis

arXiv:2607.07467v1 Announce Type: new Abstract: Spatial and Single-cell transcriptomics are transformative in deciphering cellular dynamics. As the fundamental paradigm for reconstructing cell develop

SpaR3D-MoE: Adaptive 3D Spatial Reasoning from Sparse Views Meets Geometry-Inductive Mixture-of-Experts

arXiv:2607.06620v1 Announce Type: cross Abstract: Recent Multimodal Large Language Models (MLLMs) struggle to bridge the representational gap between 2D semantic understanding and 3D spatial geometry.

Sparse Attention for Dense Open-Vocabulary Prediction in CLIP

arXiv:2607.07135v1 Announce Type: new Abstract: Contrastive Language-Image Pre-training (CLIP) relies on softmax-based self-attention, a strictly positive distribution that assigns probability mass to

local-aiarxiv-cs-cv

Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity

arXiv:2607.07386v1 Announce Type: new Abstract: Linear attention models allow a fixed state size and a fixed amount of compute per token. However, due to their limited state size, linear attention mod

researcharxiv-cs-lg

Spatiotemporal Semantic V2X Framework for Cooperative Collision Prediction

arXiv:2601.17216v3 Announce Type: replace-cross Abstract: Intelligent Transportation Systems (ITS) demand real-time collision prediction to ensure road safety and reduce accident severity. Conventiona

SPEAR: A Simulator for Photorealistic Embodied AI Research

arXiv:2607.06701v1 Announce Type: cross Abstract: Interactive simulators have become powerful tools for training embodied agents and generating synthetic visual data, but existing photorealistic simul

Specification Grounding Drives Test Effectiveness for LLM Code

arXiv:2607.06636v1 Announce Type: cross Abstract: Large language models frequently generate code that appears correct on typical inputs yet fails on edge cases, invalid inputs, and other specification

Tutorials

SPECTRA: Context-Conditioned Spectral Movement Primitives for Robot Skill Generalization

arXiv:2607.06978v1 Announce Type: new Abstract: Robot imitation learning for manipulation should preserve demonstrated task geometry while producing dynamically admissible robot motions. Existing pipe

tutorialsarxiv-cs-ro

SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation

arXiv:2607.06949v1 Announce Type: new Abstract: Training robust handwriting recognition (HTR) systems requires massive amounts of annotated data, which is often difficult to acquire. While synthetic h

Stability of Flow Models for Graph Signals

arXiv:2607.07510v1 Announce Type: cross Abstract: Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While f

applicationsarxiv-cs-ai

Stage-Aware Adaptation and Distribution Calibration for Subject-Driven Personalized Text-to-Image Generation

model-releasesarxiv-cs-cv

arXiv:2607.07173v1 Announce Type: new Abstract: Subject-driven personalized text-to-image generation requires a pretrained diffusion model to acquire a specific subject from a few reference images whi