Search: “pretraining”

NTIRE 2026 Rip Current Detection and Segmentation (RipDetSeg) Challenge Report

arXiv:2604.17070v1 Announce Type: new Abstract: This report presents the NTIRE 2026 Rip Current Detection and Segmentation (RipDetSeg) Challenge, which targets automatic rip current understanding in i

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ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization

DGX agent

arXiv:2604.17512v1 Announce Type: new Abstract: Serialization formats designed for document interchange impose structural overhead that becomes prohibitive when large language models consume operation

researcharxiv-cs-cl

21 Apr 2026

OVOD-Agent: A Markov-Bandit Framework for Proactive Visual Reasoning and Self-Evolving Detection

arXiv:2511.21064v2 Announce Type: replace-cross Abstract: Open-Vocabulary Object Detection (OVOD) aims to enable detectors to generalize across categories by leveraging semantic information. Although

Agents

Perspective-Equivariant Fine-tuning for Multispectral Demosaicing without Ground Truth

arXiv:2603.01332v2 Announce Type: replace Abstract: Multispectral demosaicing is crucial to reconstruct full-resolution spectral images from snapshot mosaiced measurements, enabling real-time imaging

agentsarxiv-cs-cv

PoliLegalLM: A Technical Report on a Large Language Model for Political and Legal Affairs

arXiv:2604.17543v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challeng

safetyarxiv-cs-cl

ReCap: Lightweight Referential Grounding for Coherent Story Visualization

arXiv:2604.18575v1 Announce Type: new Abstract: Story Visualization aims to generate a sequence of images that faithfully depicts a textual narrative that preserve character identity, spatial configur

Applications

ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control

arXiv:2604.16677v1 Announce Type: new Abstract: Vision-language-action (VLA) models have emerged as generalist robotic controllers capable of mapping visual observations and natural language instructi

applicationsarxiv-cs-ro

Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models

model-releasesarxiv-cs-lg

arXiv:2604.16775v1 Announce Type: new Abstract: Every prediction from a generative medical event model is bounded by how clinical events are tokenized, yet input representation is rarely isolated from

Residual Diffusion Bridge Model for Image Restoration

arXiv:2510.23116v3 Announce Type: replace Abstract: Diffusion bridge models establish probabilistic paths between arbitrary paired distributions and exhibit great potential for universal image restora

Safety, Security, and Cognitive Risks in State-Space Models: A Systematic Threat Analysis with Spectral, Stateful, and Capacity Attacks

arXiv:2604.16424v1 Announce Type: cross Abstract: State-Space Models (SSMs) -- structured SSMs (S4, S4D, DSS, S5), selective SSMs (Mamba, Mamba-2), and hybrid architectures (Jamba) -- are deployed in

safetyarxiv-cs-cl

Local Ai

Spatial-Regularization-Aware Dual-Branch Collaborative Inference for Training-Free OVSS in Remote Sensing Imagery

arXiv:2601.21159v2 Announce Type: replace Abstract: High-resolution remote sensing images contain densely distributed objects with pronounced scale variations and complex boundaries, which impose high

local-aiarxiv-cs-cv

Spectral Forensics of Diffusion Attention Graphs for Copy-Move Forgery Detection

arXiv:2604.17287v1 Announce Type: new Abstract: Copy-move forgery, where a region within an image is duplicated to hide or fabricate content, remains a persistent threat to visual media integrity. We

Local Ai

ST-pi: Structured SpatioTemporal VLA for Robotic Manipulation

arXiv:2604.17880v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved great success on general robotic tasks, but still face challenges in fine-grained spatiotemporal man

local-aiarxiv-cs-cv

SynAgent: Generalizable Cooperative Humanoid Manipulation via Solo-to-Cooperative Agent Synergy

arXiv:2604.18557v1 Announce Type: new Abstract: Controllable cooperative humanoid manipulation is a fundamental yet challenging problem for embodied intelligence, due to severe data scarcity, complexi

Test-Time Adaptation for EEG Foundation Models: A Systematic Study under Real-World Distribution Shifts

model-releasesarxiv-cs-lg

arXiv:2604.16926v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have shown strong potential for learning generalizable representations from large-scale neural data, yet

UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models

arXiv:2604.18518v1 Announce Type: new Abstract: Uniform Discrete Diffusion Model (UDM) has recently emerged as a promising paradigm for discrete generative modeling; however, its integration with rein

Tutorials

UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules

arXiv:2506.03157v4 Announce Type: replace-cross Abstract: Molecular Dynamics (MD) simulations are essential for understanding the atomic-level behavior of molecular systems, giving insights into their

tutorialsarxiv-cs-lg

ViPS: Video-informed Pose Spaces for Auto-Rigged Meshes

arXiv:2604.17623v1 Announce Type: new Abstract: Kinematic rigs provide a structured interface for articulating 3D meshes, but they lack an inherent representation of the plausible manifold of joint co

When Earth Foundation Models Meet Diffusion: An Application to Land Surface Temperature Super-Resolution

arXiv:2604.16841v1 Announce Type: new Abstract: Land surface temperature (LST) super-resolution is important for environmental monitoring. However, it remains challenging as coarse thermal observation

When Spike Sparsity Does Not Translate to Deployed Cost: VS-WNO on Jetson Orin Nano

model-releasesarxiv-cs-lg

arXiv:2604.17040v1 Announce Type: new Abstract: Spiking neural operators are appealing for neuromorphic edge computing because event-driven substrates can, in principle, translate sparse activity into

Agents

XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments

arXiv:2604.18484v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex

agentsarxiv-cs-cv

Causal Bootstrapped Alignment for Unsupervised Video-Based Visible-Infrared Person Re-Identification

arXiv:2604.15631v1 Announce Type: new Abstract: VVI-ReID is a critical technique for all-day surveillance, where temporal information provides additional cues beyond static images. However, existing a

Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards

arXiv:2510.07774v3 Announce Type: replace Abstract: In this paper, we observe that current models are susceptible to reward hacking, leading to a substantial overestimation of a model's reasoning abil

researcharxiv-cs-cl

Differential privacy representation geometry for medical image analysis

arXiv:2603.01098v2 Announce Type: replace-cross Abstract: Differential privacy (DP)'s effect in medical imaging is typically evaluated only through end-to-end performance, leaving the mechanism of pri

researcharxiv-cs-ai

Do LLMs Really Know What They Don't Know? Internal States Mainly Reflect Knowledge Recall Rather Than Truthfulness

arXiv:2510.09033v3 Announce Type: replace Abstract: Recent work suggests that LLMs 'know what they don't know', positing that hallucinated and factually correct outputs arise from distinct internal pr

researcharxiv-cs-cl

Earlier this year Yann LeCun left Meta because Mark Zuckerberg wouldn't bet the company on JEPA. Last week his group dropped the first JEPA …

model-releasesyann-lecun--x

Earlier this year Yann LeCun left Meta because Mark Zuckerberg wouldn't bet the company on JEPA. Last week his group dropped the first JEPA that actually trains end-to-end from raw pixels. 15 million

Find, Fix, Reason: Context Repair for Video Reasoning

arXiv:2604.16243v1 Announce Type: new Abstract: Reinforcement learning has advanced video reasoning in large multi-modal models, yet dominant pipelines either rely on on-policy self-exploration, which

GenHSI: Controllable Generation of Human-Scene Interaction Videos

arXiv:2506.19840v2 Announce Type: replace Abstract: Large-scale pre-trained video diffusion models have exhibited remarkable capabilities in diverse video generation. However, existing solutions face

MMGait: Towards Multi-Modal Gait Recognition

arXiv:2604.15979v1 Announce Type: new Abstract: Gait recognition has emerged as a powerful biometric technique for identifying individuals at a distance without requiring user cooperation. Most existi

Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction

arXiv:2604.15694v1 Announce Type: new Abstract: Discrete diffusion models based on continuous-time Markov chains (CTMCs) have shown strong performance on language and discrete data generation, yet exi

researcharxiv-cs-lg

Tutorials

OT on the Map: Quantifying Domain Shifts in Geographic Space

arXiv:2604.16220v1 Announce Type: new Abstract: In computer vision and machine learning for geographic data, out-of-domain generalization is a pervasive challenge, arising from uneven global data cove

tutorialsarxiv-cs-lg

Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning

arXiv:2509.25300v4 Announce Type: replace-cross Abstract: While scaling laws for large language models (LLMs) during pre-training have been extensively studied, their behavior under reinforcement lear

researcharxiv-cs-ai

Applications

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation

arXiv:2604.16197v1 Announce Type: new Abstract: Data attribution and valuation are critical for understanding data-model synergy for Large Language Models (LLMs), yet existing gradient-based methods s

applicationsarxiv-cs-lg

SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos

arXiv:2602.05638v3 Announce Type: replace Abstract: While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that w

UA-Net: Uncertainty-Aware Network for TRISO Image Semantic Segmentation

arXiv:2604.15542v1 Announce Type: new Abstract: Tristructural isotropic (TRISO)-coated particle fuels undergo dimensional changes and chemical reactions during high-temperature neutron irradiation. Po

Winner of CVPR2026 NTIRE Challenge on Image Shadow Removal: Semantic and Geometric Guidance for Shadow Removal via Cascaded Refinement

arXiv:2604.16177v1 Announce Type: new Abstract: We present a three-stage progressive shadow-removal pipeline for the CVPR2026 NTIRE WSRD+ challenge. Built on OmniSR, our method treats deshadowing as i

Applications

Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography

arXiv:2604.15096v1 Announce Type: new Abstract: Echocardiography is a widely used modality for cardiac assessment due to its non-invasive and cost-effective nature, but the sparse and heterogeneous sp

applicationsarxiv-cs-cv

Beyond Prompts: Unconditional 3D Inversion for Out-of-Distribution Shapes

arXiv:2604.14914v1 Announce Type: new Abstract: Text-driven inversion of generative models is a core paradigm for manipulating 2D or 3D content, unlocking numerous applications such as text-based edit

Class Unlearning via Depth-Aware Removal of Forget-Specific Directions

arXiv:2604.15166v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted knowledge from a trained model without the cost of retraining from scratch. In class unlearning, however, red

Co-distilled attention guided masked image modeling with noisy teacher for self-supervised learning on medical images

arXiv:2604.14506v1 Announce Type: new Abstract: Masked image modeling (MIM) is a highly effective self-supervised learning (SSL) approach to extract useful feature representations from unannotated dat

CobwebTM: Probabilistic Concept Formation for Lifelong and Hierarchical Topic Modeling

model-releasesarxiv-cs-cl

arXiv:2604.14489v1 Announce Type: new Abstract: Topic modeling seeks to uncover latent semantic structure in text corpora with minimal supervision. Neural approaches achieve strong performance but req

Agents

Empowerment Gain and Causal Model Construction: Children and adults are sensitive to controllability and variability in their causal interventions

arXiv:2512.08230v2 Announce Type: replace Abstract: Learning about the causal structure of the world is a fundamental problem for human cognition. Causal models and especially causal learning have pro

agentsarxiv-cs-ai

Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization

arXiv:2604.14267v1 Announce Type: new Abstract: Search agents extend Large Language Models (LLMs) beyond static parametric knowledge by enabling access to up-to-date and long-tail information unavaila

safetyarxiv-cs-lg

Local Ai

GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens

arXiv:2604.15284v1 Announce Type: new Abstract: The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representa

local-aiarxiv-cs-cv

KVNN: Learnable Multi-Kernel Volterra Neural Networks

arXiv:2604.15141v1 Announce Type: new Abstract: Higher-order learning is fundamentally rooted in exploiting compositional features. It clearly hinges on enriching the representation by more elaborate

Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents

arXiv:2604.14717v1 Announce Type: cross Abstract: Persistent language-model agents increasingly combine tool use, tiered memory, reflective prompting, and runtime adaptation. In such systems, behavior

safetyarxiv-cs-lg

Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

arXiv:2604.14206v1 Announce Type: new Abstract: This paper proposes a machine learning assisted portfolio optimization framework designed for low data environments and regime uncertainty. We construct

researcharxiv-cs-lg

Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings

arXiv:2604.14547v1 Announce Type: new Abstract: Objective: Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Early prediction of P

researcharxiv-cs-lg