Search: “framework”

Alpha-R1: Alpha Screening with LLM Reasoning via Reinforcement Learning

arXiv:2512.23515v2 Announce Type: replace-cross Abstract: Signal decay and regime shifts pose recurring challenges for data-driven investment strategies in non-stationary markets, where conventional t

safetyarxiv-cs-lg

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Agents

An Exploratory Study of Frequency-Aware Task Weighting for YOLOv8-Based Unified Driving Perception

DGX agent

arXiv:2609.05516v1 Announce Type: new Abstract: Unified perception enables autonomous driving systems to perform object detection, drivable-area segmentation, and lane segmentation within a single net

agentsarxiv-cs-cv

9 Sept 2026

An overview of 3D Vision-Language Models

arXiv:2609.05583v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and

Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning

arXiv:2609.09030v1 Announce Type: cross Abstract: Chain-of-thought reasoning provides a structured computation between a model's input and final answer. Yet it is often evaluated through endpoint accu

AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots

arXiv:2603.07648v2 Announce Type: replace-cross Abstract: Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robo

applicationsarxiv-cs-cv

AURORA: Active Uncertainty-Driven Re-Orientation for In-Hand Reconstruction

arXiv:2609.08493v1 Announce Type: cross Abstract: Observing objects grasped by a robot hand is challenging due to severe visual occlusions. Although in-hand manipulation can expose hidden surfaces, ex

Automatic Red Teaming for Implicit Vulnerabilities of Text-to-Image Models

arXiv:2609.06094v1 Announce Type: new Abstract: Red-teaming Text-to-Image (T2I) models is essential for safe deployment, yet it remains particularly challenging against implicit adversarial prompts. U

AVSplat: Dense-View Feed-Forward 3D Gaussian Splatting with Assist-View Preconditioning

arXiv:2609.05925v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting enables novel view synthesis from uncalibrated multi-view images. Although more views should improve perfor

Bayesian Matrix-Valued Graphs for Context-Dependent Multivariate Relationships

arXiv:2609.08055v1 Announce Type: cross Abstract: Many scientific graphs attach several variables to each node, so a single scalar edge weight cannot describe direction-dependent interactions. We mode

Benchmarking Dexterity of Multifingered Robot Hands: A Review and Perspective

model-releasesarxiv-cs-ro

arXiv:2609.05585v1 Announce Type: new Abstract: Robot hands are a key interface between AI and the physical world, making advances in robotic dexterity essential to realizing the vision of physical AI

Best-of-Both Worlds for linear contextual bandits with paid observations

arXiv:2510.07424v3 Announce Type: replace Abstract: We study linear contextual bandits with paid observations, where at each round the learner observes a context, selects an action, and may pay a fixe

Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation

arXiv:2609.07720v1 Announce Type: new Abstract: Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both visual identity and character behavior-req

agentsarxiv-cs-cv

Bi-HYCO: Bi-Objective Cooperative Learning for PDE Parameter Identification under Fragmented Observations

arXiv:2609.06511v1 Announce Type: new Abstract: Physical and synthetic models may describe complementary aspects of the same PDE-governed system while receiving different, possibly fragmented, observa

BIFTA: Brain-Inspired Few-Shot Tactile Adaptation for Unknown Sensors

arXiv:2609.08673v1 Announce Type: new Abstract: Advances in tactile sensing have made contact-rich perception possible, accelerating progress in robotic manipulation, material understanding, and embod

researcharxiv-cs-ro

Branch-Centric Tokenization and Test-Time Augmentation for Skeleton Generation

arXiv:2609.06218v1 Announce Type: new Abstract: Automatic skeleton generation involves predicting both joint positions and skeletal connectivity. However, existing approaches struggle to encode branch

Budgeted Task-Aware Acquisition of Dynamic Networks

arXiv:2609.05862v1 Announce Type: new Abstract: Learning on dynamic graphs is difficult when changes in the underlying network are only partially observed. Acquiring current graph information incurs o

Can People Distinguish Human and AI Agency in Humanoid Teleoperation? A Preliminary Study of Agency Perception

arXiv:2609.06434v1 Announce Type: cross Abstract: Can people distinguish between human and AI agency in humanoid teleoperation? To explore this question, we developed extit{Ghost-in-the-Loop}, a teleo

researcharxiv-cs-ro

Tutorials

Capsule Lens: Locating and Tracking Concept Geometry in Model Representations

arXiv:2609.05575v1 Announce Type: cross Abstract: Understanding how concepts are encoded in the internal representations of machine learning models is a central problem in mechanistic interpretability

tutorialsarxiv-cs-cv

CAR-MIL: Counterfactual Attention Regularization for Multiple Instance Learning

arXiv:2609.08419v1 Announce Type: new Abstract: Multiple Instance Learning (MIL) is widely used for weakly supervised learning, particularly in digital pathology, where fine-grained annotations are co

CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation

arXiv:2603.00039v2 Announce Type: replace Abstract: LLM-as-a-judge ensembles are the standard paradigm for scalable evaluation, but their aggregation mechanisms suffer from a fundamental flaw: they im

Causal DAG Identification for Count Data via Poisson Thinning Structural Equation Models

arXiv:2609.06098v1 Announce Type: cross Abstract: Count-valued variables arise in many scientific and applied settings, yet explicit structural models that allow full identification of causal DAGs fro

CausalChapter: Improving Long-Video Chaptering with Interventional Dependency Modeling

arXiv:2609.08686v1 Announce Type: new Abstract: Long-form instructional videos require automatic chaptering to support browsing, navigation, and knowledge access. Recent long-context language models c

Certifying cooperation: a novel approach to cooperative multi-agent task generation

arXiv:2609.06586v1 Announce Type: cross Abstract: A shared reward gives agents a common objective, but leaves open when, how and even whether they must cooperate to succeed. We address these questions

agentsarxiv-cs-lg

ChatBEV: Empowering Traffic Scene Understanding and Simulation via Vision-Language Model

arXiv:2503.13938v3 Announce Type: replace Abstract: Comprehensive traffic scene understanding is a foundational capability for Intelligent Transportation Systems (ITS) underpinning applications such a

CHILD: Human-in-the-Loop OOD Detection for Safe Clinical Deployment

arXiv:2609.07188v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection is critical for safe deployment of medical AI systems. Recently, test-time adaptation (TTA) has emerged as a new par

CogniDir: Combating Cognitive Malicious Comments via Adaptive Distributional Learning for Robust Fake News Detection

arXiv:2510.09712v4 Announce Type: replace Abstract: The proliferation of Large Language Models (LLMs) has enabled a new class of psychologically grounded malicious comments, shifting fake news attacks

safetyarxiv-cs-lg

Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation

arXiv:2609.06433v1 Announce Type: new Abstract: The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the

safetyarxiv-cs-ro

Tutorials

Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRI

arXiv:2609.06807v1 Announce Type: new Abstract: In this work, we comprehensively evaluate three popular feature-extraction paradigms in AI-based neuroimaging modeling: (1) computation of anatomical su

tutorialsarxiv-cs-cv

ComVLA: Communication-Aware Split Inference for VLA Models in 6G-Connected Robotics

model-releasesarxiv-cs-ro

arXiv:2609.07838v1 Announce Type: new Abstract: Connected robotics is an emerging 6G application where mobile robots follow natural-language instructions to manipulate physical objects. The Vision-Lan

Local Ai

Connectome-to-Function: Conditional Generative Latent Representations for Reservoir Computing

arXiv:2609.06093v1 Announce Type: new Abstract: Connectomes, graph-level maps of neurons and their synaptic connections, provide a structural basis for understanding how brain circuits support functio

local-aiarxiv-cs-lg

ContactWorld: What Representations Matter in Vision-Tactile World Models for Contact-Rich Manipulation

arXiv:2606.13877v2 Announce Type: replace Abstract: Contact-rich manipulation requires world models to capture complex interaction dynamics from heterogeneous visual and tactile observations, yet the

applicationsarxiv-cs-ro

ContextFlow: In-Context Flow Matching for Robot Manipulation

arXiv:2609.06852v1 Announce Type: new Abstract: Although highly effective in vision and language domains, applying in-context learning to robotics remains challenging. Existing autoregressive in-conte

researcharxiv-cs-ro

CONTHER: Context-Aware Reinforcement Learning for Robotic Manipulation with Sparse Rewards

arXiv:2503.15895v2 Announce Type: replace Abstract: This paper investigates whether sequential context improves goal-conditioned Reinforcement Learning in sparse-reward manipulation tasks. While Hinds

safetyarxiv-cs-ro

Continual Policy Consolidation for Lifelong Robot Learning

arXiv:2601.22475v2 Announce Type: replace Abstract: Building a generalist robot policy requires continuously integrating new skills while preserving previously acquired behaviors. Directly optimizing

safetyarxiv-cs-lg

ControlTac: Scaling Tactile Data with Physically Controlled Tactile Image Generation

arXiv:2505.20498v3 Announce Type: replace Abstract: Vision-based tactile sensing is widely used in perception, reconstruction, and robotic manipulation, yet collecting large-scale tactile data remains

applicationsarxiv-cs-cv

CoordFormer: Give Me Any Coordinates and I Will Give You Labels

arXiv:2609.08660v1 Announce Type: new Abstract: Semantic segmentation on very-high-resolution images remains challenging due to the high computational cost and the difficulty of capturing fine-grained

CoRe-SAM3: Conditional Semantic--Visual Reconciliation for SAM3 Crack Segmentation

arXiv:2609.05816v1 Announce Type: new Abstract: Crack segmentation requires a model to recognize target semantics while accurately recovering thin, low-contrast, and topologically continuous local str

CoRL: Co-Evolutionary Reinforcement Learning for Adaptive Indirect Prompt-Injection Attacks and Defenses

arXiv:2609.07529v1 Announce Type: new Abstract: Tool-augmented language agents are vulnerable to indirect prompt injection (IPI). Unlike direct prompt injection, IPI hides adversarial instructions in

CR-VLA-Force: Learning Control-aware Compliance VLA Model for Robust Contact-rich Robotic Manipulation

arXiv:2609.05832v1 Announce Type: new Abstract: Integrating visuomotor policies or Vision-Language-Action (VLA) models with force/torque (F/T) perception has demonstrated significant progress in imita

safetyarxiv-cs-ro

CST-WM: A Causally Structured World Model for Embodied Visual Tracking

arXiv:2609.06302v1 Announce Type: new Abstract: Embodied visual tracking requires a robot not only to react to the current view, but to choose actions that preserve or recover future evidence of a mov

CUNO: Curriculum and Preference Optimization for Stable Graph Unlearning under Mass Deletion

arXiv:2609.08244v1 Announce Type: new Abstract: Graph unlearning removes the influence of designated training data from a trained graph model without retraining from scratch. However, existing methods

CUSP: Decomposable Collective Uncertainty for Multi-Agent Multimodal Reasoning

arXiv:2609.05708v1 Announce Type: cross Abstract: Aggregating heterogeneous vision-language models (VLMs) can improve multimodal reasoning, but neither an individual model's confidence nor that of the

agentsarxiv-cs-lg

CVT-GS: Learning to Simplify 3D Gaussian Splatting with Centroidal Voronoi Tessellation

arXiv:2609.08730v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time novel view synthesis, rendering high-fidelity scenes often rel

DAGLFNet: Deep Feature Attention Guided Global and Local Feature Fusion for Pseudo-Image Point Cloud Segmentation

arXiv:2510.10471v3 Announce Type: replace Abstract: Environmental perception systems are crucial for high-precision mapping and autonomous navigation, with LiDAR serving as a core sensor providing acc

agentsarxiv-cs-cv

Local Ai

DART: Distributional Adversarial Recurrent Training for Algorithm Learning

arXiv:2609.05988v1 Announce Type: new Abstract: Recurrent reasoning models (RRMs) can solve structured problems, achieving easy-to-hard generalization through iterative computation in hidden space. Th

local-aiarxiv-cs-lg

Data Efficient Sample Selection for In-Context Learning

arXiv:2609.06670v1 Announce Type: new Abstract: The In-context learning (ICL) paradigm aids large language models (LLMs) to adapt to new tasks without need for fine-tuning. However, selecting an optim

Data Quality Rule Generation with LLMs

arXiv:2609.06053v1 Announce Type: new Abstract: The validation of data, such as customer and employee data, is an important task in many organizations. Errors in data can have severe consequences. For

applicationsarxiv-cs-lg

DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space

arXiv:2509.25180v3 Announce Type: replace Abstract: Existing text-to-image diffusion models excel at generating high-quality images, but face significant efficiency challenges when scaled to high reso