Search: “framework”

BridgeCast: Bridging Ocean Wave Forecasts to Reanalysis via Flow Matching with Exogenous Variables

arXiv:2610.03759v1 Announce Type: cross Abstract: Ocean wave forecasting is essential for maritime safety, offshore operations, and coastal resilience, yet remains challenging due to systematic biases

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Tutorials

Broaden Your Views for Self-Supervised Video Learning

DGX agent

arXiv:2103.16559v3 Announce Type: cross Abstract: Most successful self-supervised learning methods are trained to align the representations of two independent views from the data. State-of-the-art met

tutorialsarxiv-cs-lg

6 Oct 2026

ChronoWorld: Camera-Controlled Consistent 4D World Generation via Spatiotemporal Cues and Geometric Reflections

arXiv:2610.06687v1 Announce Type: new Abstract: While existing camera-controllable video generation models can produce visually compelling sequences, preserving intrinsic 4D spatiotemporal coherence r

researcharxiv-cs-cv

ClasSAE: Class-Aligned Sparse Autoencoders via Differentiable Feature-Class Affinity

arXiv:2610.04020v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) began as an unsupervised tool for decomposing neural representations into sparse, interpretable features, and are increasingl

safetyarxiv-cs-cv

CleanMDM: Clean Motion Diffusion Model for Multimodal Motion Cleanup

arXiv:2610.05411v1 Announce Type: new Abstract: Motion capture data is rarely directly usable, as they typically exhibit missing segments, jitter, drift and contact artifacts. Traditionally, corrupted

researcharxiv-cs-cv

Climate Surrogates for Scalable Multi-Agent Reinforcement Learning: A Case Study with CICERO-SCM

arXiv:2510.07971v2 Announce Type: replace Abstract: Climate policy analysis requires models that capture multi-gas climate effects, but such models are too slow to embed in reinforcement learning loop

CoDance: Learning Reactive and Compliant Human-Humanoid Interaction from Video

arXiv:2610.05324v1 Announce Type: cross Abstract: Partnered human-humanoid interaction couples locomotion with continuous physical contact. A humanoid needs to coordinate with a person's motion while

Code2Games: Enabling Coding Agents for Gaming World Generation

arXiv:2610.05033v1 Announce Type: new Abstract: Generating a high-quality gaming world from a natural-language game intent requires joint reasoning about scene structure, spatial layout, gameplay obje

CodeForge-MA: Execution-Verified Multi-Agent Learning with Language-Conditioned LoRA for Multilingual Code Generation

arXiv:2610.05481v1 Announce Type: cross Abstract: Large language models for code generation often fail on execution, multilingual coverage, and contamination control, especially under frozen backbone

Applications

Communication-Efficient Relative Pose Estimation with Vision Foundation Models for Ephemeral Collaborative Perception

arXiv:2607.14539v2 Announce Type: replace Abstract: Relative pose estimation is a fundamental capability for collaborative perception and coordination in multi-robot systems. However, robots encounter

applicationsarxiv-cs-ro

Compact set-valued deep ensembling in multi-class classification

arXiv:2610.05332v1 Announce Type: new Abstract: This paper tackles visible challenges in deep ensemble learning, where deep neural networks serve as ensemble members: training and storage burdens, and

Component-Level Evaluation of Adaptive PINN Training for CFD-Oriented Crystal Growth Simulation

arXiv:2610.05127v1 Announce Type: new Abstract: Physics-informed neural network (PINN) training minimizes a weighted combination of partial differential equation (PDE), boundary-condition, and initial

Conditional Trajectory Peaks: Single-Pass Multimodal Policies over Action Chunks

arXiv:2610.06104v1 Announce Type: new Abstract: Multimodal imitation learning requires diverse executable futures under the same observation and consistent behavior across replanning cycles. We presen

safetyarxiv-cs-ro

ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution

arXiv:2610.04605v1 Announce Type: new Abstract: Many visual explanation methods in computer vision highlight pixel importance but struggle to link these low-level cues to semantically meaningful conce

safetyarxiv-cs-cv

Conformal Prediction with Paraphrase-Aware Scoring for LLM Uncertainty Quantification

arXiv:2610.04239v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) for large language models (LLMs) aims to provide reliable measures of predictive confidence, yet current methods are o

Contrastive Time Series Forecasting with Anomalies

arXiv:2512.11526v2 Announce Type: replace Abstract: Time series forecasting predicts future values from past data. In real-world settings, some anomalous events have lasting effects and influence the

Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation

model-releasesarxiv-cs-ro

arXiv:2610.06171v1 Announce Type: new Abstract: Evaluating end-to-end autonomous driving under rare, safety-critical vehicle-pedestrian interactions requires photorealistic, sensor-level scenarios. Ho

Controllable Road Marking Generation

arXiv:2610.05771v1 Announce Type: new Abstract: Lane and road markings provide critical guidance for vehicle navigation and multi-agent coordination, yet authoring them at scale remains a manual workf

Coupling Noisy Pairwise Knowledge to the DAG Posterior for Causal Discovery

arXiv:2610.04559v1 Announce Type: new Abstract: External causal reports can improve structure learning from limited observations, but their reliability varies across sources and variable pairs. We int

Cross-Modal Contrastive Learning for the Retrieval of Immunotherapy-Associated Molecular Signatures from Histopathology

arXiv:2610.05157v1 Announce Type: new Abstract: Gastric Adenocarcinoma is a leading cause of cancer mortality. Although 'Inflamed/Non-Inflamed' subtypes have been proposed to predict immunotherapy res

CURIO: Curiosity-Driven Test-Time Learning for Open-Ended Discovery

arXiv:2610.04851v1 Announce Type: new Abstract: Open-ended discovery requires learning from repeated attempts while continuing to explore directions whose value is not yet apparent. Search with a froz

Decoupling Time and Space: A Temporally Conditioned Refinement for EEG Source Imaging

arXiv:2610.06726v1 Announce Type: new Abstract: Electroencephalography (EEG) offers millisecond temporal resolution, but inferring underlying neural sources is a severely ill-posed spatial inverse pro

local-aiarxiv-cs-lg

Deep Prior Learning for Embodied Perception

arXiv:2610.05531v1 Announce Type: new Abstract: Embodied systems need geometric perception that exploits available observations beyond images alone. Recent feed-forward 3D models incorporate geometric

DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection

arXiv:2511.04086v2 Announce Type: replace Abstract: With the rapid growth of graph-structured data in critical domains, unsupervised graph-level anomaly detection (UGAD) has become a pivotal task. UGA

Tutorials

DexForge: High-Fidelity Physics-Informed Dexterous Retargeting

arXiv:2610.06331v1 Announce Type: new Abstract: Human demonstrations offer rich examples of precise dexterous manipulation and a promising source of robot training data. However, high-fidelity reprodu

tutorialsarxiv-cs-ro

Agents

Difference Feature Map Distillation: Transferring Inter-Sample Relational Knowledge Towards Efficient Transformer-Based Tracking

arXiv:2610.05707v1 Announce Type: new Abstract: In autonomous driving perception, visual object tracking systems must satisfy stringent latency and power constraints while remaining robust in complex

agentsarxiv-cs-cv

Agents

Differentiable Ternary Temporal Logic Semantics with Polynomial Surrogate Networks

arXiv:2610.04662v1 Announce Type: cross Abstract: Temporal logic provides designers a formal reasoning tool for specifying complex spatio-temporal behaviors and tasks for autonomous systems. Many tech

agentsarxiv-cs-ro

dIon: Fragmentation-Based Invariance for Self-Supervised Learning of Tandem Mass Spectra

arXiv:2610.06282v1 Announce Type: new Abstract: We introduce a novel invariance for peptide tandem mass spectrometry data, unlocking self-supervised representation learning that improves de novo seque

Discovered, Not Designed: Population Evolution for Collaborative and Compute-Intensive Model Discovery

arXiv:2610.05950v1 Announce Type: new Abstract: LLM-driven evolution enables iterative model development, but two practical goals remain underexplored: finding model designs that transfer across relat

local-aiarxiv-cs-lg

Dissecting Quantization Error: A Concentration-Alignment Perspective

arXiv:2603.04359v2 Announce Type: replace Abstract: Quantization can drastically increase the efficiency of large language and vision models, but typically incurs an accuracy drop. Recently, function-

DriftSR: One-Step Real-World Image Super-Resolution via Distribution Drifting

arXiv:2610.04819v1 Announce Type: new Abstract: One-step real-world image super-resolution (Real-ISR) offers efficient inference, but recovering realistic and perceptually rich details often relies on

local-aiarxiv-cs-cv

Agents

DUET: Co-Evolving Solver and Grader Agents

arXiv:2610.04087v1 Announce Type: new Abstract: Agentic workflows are increasingly used across domains such as technology, finance, and enterprise operations. As these agents become more widely deploy

agentsarxiv-cs-lg

DV-Lens: Revealing the Functional Organization of Language Model Parameters

arXiv:2610.04489v1 Announce Type: cross Abstract: Understanding parameter functions helps elucidate the internal mechanisms of large language models (LLMs). However, how to connect parameters from dif

Dynamic Minimax Regret Optimization for Robust LLM Post-Training

arXiv:2610.06329v1 Announce Type: new Abstract: Modern LLM training increasingly relies on heterogeneous data sources spanning different domains, tasks, preference distributions, and difficulty levels

EchoDino: A pediatric foundation model for transferable echocardiographic analysis across the lifespan

arXiv:2610.05603v1 Announce Type: new Abstract: Echocardiography is the most widely used cardiac imaging modality, yet interpretation demands integrating visual evidence across global anatomy, localiz

local-aiarxiv-cs-cv

EEGDM: Label-Efficient EEG Representation Learning with Generative Diffusion Model

arXiv:2508.14086v4 Announce Type: replace Abstract: Electroencephalography (EEG) is a critical tool for monitoring brain activity and diagnosing neurological disorders such as epilepsy. However, learn

Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts

arXiv:2610.06147v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot transferability but remain vulnerable to target-domain shifts at inference time. Test-time adapta

EfficientXpert: Efficient Domain Adaptation for Large Language Models via Propagation-Aware Pruning

arXiv:2511.19935v3 Announce Type: replace Abstract: Deploying domain-specialized large language models on resource-constrained hardware motivates reducing both adaptation cost and the number of retain

Encoded but Not in Control: Revealing the Grounding Gap in Vision-Language Robot Policies

arXiv:2610.06235v1 Announce Type: cross Abstract: Instruction following is central to language-conditioned robot policies: language should determine what to do when the same scene permits multiple val

End-to-End Autonomous Recursive Arborescence Deformable Flow and Non-Linear Hemodynamics for Patient-Specific Coronary Centerline Extraction

arXiv:2610.05900v1 Announce Type: new Abstract: Extracting patient-specific vascular trees from volumetric medical images is fundamental to computational angiography and non-invasive hemodynamic asses

local-aiarxiv-cs-cv

End-to-End Safe Social Navigation via Multi-Task Reinforcement Learning and Probabilistic Perception

arXiv:2610.05733v1 Announce Type: new Abstract: Autonomous social navigation requires balancing efficiency, physical safety, and social compliance. Reinforcement Learning (RL) methods provide a viable

safetyarxiv-cs-ro

EndoWave: 4D Gaussian Splatting with Rational Wavelet for Endoscopic Reconstruction

arXiv:2510.23087v2 Announce Type: replace Abstract: In robot-assisted minimally invasive surgery, accurate 3D reconstruction from endoscopic video is vital for downstream tasks and improved outcomes.

researcharxiv-cs-cv

Enhancing Long-Video VLM Embeddings with Query-Aware Streaming Latent Reasoning

arXiv:2610.04864v1 Announce Type: new Abstract: Long-video embedding requires capturing sparse query-relevant evidence under a limited visual-token budget. Uniform sampling can miss brief events in vi

EpicWorldModel: Exploration-driven Planning with Latent World Models

arXiv:2610.05996v1 Announce Type: new Abstract: Latent world models based on Joint-Embedding Predictive Architecture (JEPA) are deterministic by design. While successful in fully observable scenarios,

Evolving LLM-Generated Features for Interpretable Classification

arXiv:2610.03951v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as classifiers, yet they operate as opaque systems whose decisions are difficult to interpret, which

Exploiting Hierarchical Controller Structure in Contextual Parameter Learning for Humanoid Loco-Manipulation

arXiv:2610.04609v1 Announce Type: cross Abstract: Hierarchical control architectures are widely used to decompose complex control problems into interacting control levels and are particularly importan

FACET: Factorized Asymmetric Conditioning for Efficient Transport in High-Fidelity Fluorescence Microscopy Synthesis

arXiv:2610.05353v1 Announce Type: cross Abstract: Fluorescence microscopy reveals where proteins localize, but only a limited number of proteins can be imaged in the same cell; generating these images

FADE: Frame-Aware Diffusion-Transformer-based Multi-Concept Erasure for Video Unlearning

arXiv:2610.03980v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models can reproduce copyrighted, violent, or explicit content, which motivates concept erasure: removing designated conce