Search: “framework”

SatSurfGS: Generalizable 2D Gaussian Splatting for Sparse-View Satellite Surface Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.07181v1 Announce Type: new Abstract: Sparse-view satellite image surface reconstruction remains highly challenging, fundamentally because the reliability of multi-view matching under satell

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Self-Consolidating Language Models: Continual Knowledge Incorporation from Context

DGX agent

arXiv:2605.07076v1 Announce Type: new Abstract: Large language models (LLMs) increasingly receive information as streams of passages, conversations, and long-context workflows. While longer context wi

researcharxiv-cs-cl

11 May 2026

SoLAR: Error-Resilient Streamable Long-Horizon Free-Viewpoint Video Reconstruction with Anchor Activation and Latent Recalibration

arXiv:2605.07346v1 Announce Type: new Abstract: Free-Viewpoint Video (FVV) has emerged as a cornerstone of next-generation immersive media systems and attracted widespread attention. Previous methods

Hardware

SpikingBrain: Spiking Brain-inspired Large Models

arXiv:2509.05276v4 Announce Type: replace-cross Abstract: Mainstream Transformer-based large language models face major efficiency bottlenecks: training computation scales quadratically with sequence

hardwarearxiv-cs-ai

StreamPhy: Streaming Inference of High-Dimensional Physical Dynamics via State Space Models

arXiv:2605.07384v1 Announce Type: new Abstract: Inferring the evolution of high-dimensional and multi-modal (e.g., spatio-temporal) physical fields from irregular sparse measurements in real time is a

Task-Oriented Communication for Human Action Understanding via Edge-Cloud Co-Inference

arXiv:2605.07354v1 Announce Type: cross Abstract: The expanding application of smart sensing has created a growing demand for the accurate understanding of human action at the network edge. Traditiona

The Effective Depth Paradox: Evaluating the Relationship between Architectural Topology and Trainability in Deep CNNs

arXiv:2602.13298v3 Announce Type: replace-cross Abstract: This paper investigates the relationship between convolutional neural network (CNN) topology and image recognition performance through a compa

researcharxiv-cs-ai

The Limits of AI-Driven Allocation: Optimal Screening under Aleatoric Uncertainty

arXiv:2605.07979v1 Announce Type: new Abstract: The rise of machine learning has shifted targeted resource allocation in policy and humanitarian settings toward algorithmic targeting based on predicte

Thoughts on GitLab's workforce reduction' and 'structural and strategic decisions'

GitLab Act 2 There's a lot going on in this announcement from GitLab about the 'workforce reduction' and 'structural and strategic decisions' they are making with respect to the agentic era. They're '

agentssimon-willison

TopoPrune: Robust Data Pruning via Unified Latent Space Topology

arXiv:2602.02739v2 Announce Type: replace-cross Abstract: Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geom

researcharxiv-cs-ai

Towards Highly-Constrained Human Motion Generation with Retrieval-Guided Diffusion Noise Optimization

arXiv:2605.08054v1 Announce Type: new Abstract: Generating human motion that satisfies customized zero-shot goal functions, enabling applications such as controllable character animation and behavior

Local Ai

3D Ultrasound-Derived Pseudo-CT Synthesis Using a Transformer-Augmented Residual Network for Real-Time Operator Guidance

arXiv:2605.04856v1 Announce Type: new Abstract: Computed tomography (CT) is indispensable for clinical diagnosis and image-guided interventions but exposes patients to ionizing radiation, motivating t

local-aiarxiv-cs-cv

Advancing Analytic Class-Incremental Learning through Vision-Language Calibration

arXiv:2602.13670v2 Announce Type: replace Abstract: Class-incremental learning (CIL) with pre-trained models (PTMs) faces a critical trade-off between efficient adaptation and long-term stability. Whi

safetyarxiv-cs-lg

Agent-Based Modeling of Low-Emission Fertilizer Adoption for Dairy Farm Decarbonisation using Empirical Farm Data

arXiv:2605.03648v1 Announce Type: new Abstract: To understand complex system dynamics in dairy farming, it is essential to use modeling tools that capture farm heterogeneity, social interactions, and

Anatomy of a failure: When, how, and why deep vision fails in scientific domains

arXiv:2605.04231v1 Announce Type: new Abstract: Mirroring its ubiquity in popular media and all human activities, the use of deep learning (DL) is rapidly growing in scientific imaging modalities. How

safetyarxiv-cs-cv

Automated Formal Proofs of Combinatorial Identities via Wilf-Zeilberger Guidance and LLMs

model-releasesarxiv-cs-lg

arXiv:2605.04472v1 Announce Type: new Abstract: Automating formal proofs of combinatorial identities is challenging for LLM-based provers, as long-horizon proof planning is required and unconstrained

BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference

arXiv:2605.04087v1 Announce Type: cross Abstract: Optimization over the Stiefel manifold St(p,d), the set of p imes d column-orthonormal matrices, is fundamental in statistics, machine learning, and s

Collision-Aware Object-Goal Visual Navigation via Two-Stage Deep Reinforcement Learning

arXiv:2502.13498v2 Announce Type: replace-cross Abstract: Object-goal visual navigation aims to reach a specific target object using egocentric visual observations. Recent deep reinforcement learning

agentsarxiv-cs-cv

CPCANet: Deep Unfolding Common Principal Component Analysis for Domain Generalization

arXiv:2605.05136v1 Announce Type: new Abstract: Domain Generalization (DG) aims to learn representations that remain robust under out-of-distribution (OOD) shifts and generalize effectively to unseen

tutorialsarxiv-cs-cv

Cross-Tokenizer Likelihood Scoring Algorithms for Language Model Distillation

arXiv:2512.14954v2 Announce Type: replace Abstract: Computing next-token likelihood ratios between two language models (LMs) is a standard task in training paradigms such as knowledge distillation. Si

researcharxiv-cs-cl

DiffCap-Bench: A Comprehensive, Challenging, Robust Benchmark for Image Difference Captioning

model-releasesarxiv-cs-cv

arXiv:2605.04503v1 Announce Type: new Abstract: Image Difference Captioning (IDC) generates natural language descriptions that precisely identify differences between two images, serving as a key bench

Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation

arXiv:2605.05054v1 Announce Type: new Abstract: Recent flow matching (FM) methods improve the few-shot adaptation of vision-language models, by modeling cross-modal alignment as a continuous multi-ste

safetyarxiv-cs-cv

DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation

arXiv:2605.04458v1 Announce Type: new Abstract: Evaluation of long-form, citation-backed reports has lately received significant attention due to the wide-scale adoption of retrieval-augmented generat

researcharxiv-cs-cl

From Diffusion to Rectified Flow: Rethinking Text-Based Segmentation

arXiv:2605.04590v1 Announce Type: new Abstract: Text-based image segmentation aims to delineate object boundaries within an image from text prompts, offering higher flexibility and broader application

tutorialsarxiv-cs-cv

Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation

model-releasesarxiv-cs-cl

arXiv:2605.04135v1 Announce Type: cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do. That literature answers a related, but consequenti

Applications

Gated Multimodal Learning for Interpretable Property Energy Performance Prediction and Retrofit Scenario Analysis

arXiv:2605.05088v1 Announce Type: new Abstract: Achieving resilient and sustainable cities requires scalable approaches to decarbonising residential buildings, which account for about 20% of UK greenh

applicationsarxiv-cs-lg

GLM-5V-Turbo Tech Report: Toward a Native Foundation Model for Multimodal Agents This report summarizes the main improvements behind GLM-5V-…

GLM-5V-Turbo Tech Report: Toward a Native Foundation Model for Multimodal Agents This report summarizes the main improvements behind GLM-5V-Turbo across model design, multimodal training, reinforcemen

agentszhipu-ai--x

Harnessing Linguistic Dissimilarity for Language Generalization on Unseen Low-Resource Varieties

arXiv:2605.04500v1 Announce Type: new Abstract: Low-resource language varieties used by specific groups remain neglected in the development of Multilingual Language Models. A great deal of cross-lingu

researcharxiv-cs-cl

HDFlow: Hierarchical Diffusion-Flow Planning for Long-horizon Tasks

arXiv:2605.04525v1 Announce Type: new Abstract: Recent advances in generative models have shown promise in generating behavior plans for long-horizon, sparse reward tasks. While these approaches have

tutorialsarxiv-cs-ro

Iso-Riemannian Optimization on Learned Data Manifolds

arXiv:2510.21033v2 Announce Type: replace-cross Abstract: High-dimensional data with intrinsic low-dimensional structure is ubiquitous in machine learning and data science. While various approaches al

tutorialsarxiv-cs-lg

KGLAMP: Knowledge Graph-guided Language model for Adaptive Multi-robot Planning and Replanning

model-releasesarxiv-cs-ro

arXiv:2602.04129v2 Announce Type: replace Abstract: Heterogeneous multi-robot systems are increasingly used in long-horizon missions requiring coordinated planning across diverse capabilities. However

Layerwise LQR for Geometry-Aware Optimization of Deep Networks

arXiv:2605.04230v1 Announce Type: new Abstract: Geometry-aware optimizers such as Newton and natural gradient can improve conditioning in deep learning, but scalable variants such as K-FAC, Shampoo, a

Learning reveals invisible structure in low-rank RNNs

arXiv:2605.04115v1 Announce Type: new Abstract: Learning in neural systems arises from synaptic changes that reshape the representations underlying behavior. While low-rank recurrent neural networks (

Applications

Learning Time-Inhomogeneous Markov Dynamics in Financial Time Series via Neural Parameterization

arXiv:2605.04690v1 Announce Type: new Abstract: Modeling the dynamics of non-stationary stochastic systems requires balancing the representational power of deep learning with the mathematical transpar

applicationsarxiv-cs-lg

Applications

LTGS: Long-Term Gaussian Scene Chronology From Sparse View Updates

arXiv:2510.09881v3 Announce Type: replace Abstract: Recent advances in novel-view synthesis can create the photo-realistic visualization of real-world environments from conventional camera captures. H

applicationsarxiv-cs-cv

MuCALD-SplitFed: Causal-Latent Diffusion for Privacy-Preserving Multi-Task Split-Federated Medical Image Segmentation

arXiv:2605.04108v1 Announce Type: new Abstract: Federated Learning enables decentralized training by aggregating model updates across clients without sharing raw data, while Split Federated Learning f

Hardware

Piper: Efficient Large-Scale MoE Training via Resource Modeling and Pipelined Hybrid Parallelism

arXiv:2605.05049v1 Announce Type: cross Abstract: Frontier models increasingly adopt Mixture-of-Experts (MoE) architectures to achieve large-model performance at reduced cost. However, training MoE mo

hardwarearxiv-cs-lg

Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary

arXiv:2506.00886v3 Announce Type: replace Abstract: As large language models evolve into tool-augmented agents, a central question remains unresolved: when is external tool use actually justified? Exi

agentsarxiv-cs-ai

Local Ai

Position: Embodied AI Requires a Privacy-Utility Trade-off

arXiv:2605.05017v1 Announce Type: cross Abstract: Embodied AI (EAI) systems are rapidly transitioning from simulations into real-world domestic and other sensitive environments. However, recent EAI so

local-aiarxiv-cs-ro

Predict-then-Diffuse: Adaptive Response Length for Compute-Budgeted Inference in Diffusion LLMs

arXiv:2605.04215v1 Announce Type: new Abstract: Diffusion-based Large Language Models (D-LLMs) represent a promising frontier in generative AI, offering fully parallel token generation that can lead t

safetyarxiv-cs-lg

Programmatic Context Augmentation for LLM-based Symbolic Regression

arXiv:2605.03101v1 Announce Type: new Abstract: Symbolic regression (SR), the task of discovering mathematical expressions that best describe a given dataset, remains a fundamental challenge in scient

researcharxiv-cs-ai

Quantifying Trust: Financial Risk Management for Trustworthy AI Agents

arXiv:2604.03976v2 Announce Type: replace Abstract: Prior work on trustworthy AI emphasizes model-internal properties such as bias mitigation, adversarial robustness, and interpretability. As AI syste

Redefining AI Red Teaming in the Agentic Era: From Weeks to Hours

model-releasesarxiv-cs-ai

arXiv:2605.04019v1 Announce Type: new Abstract: AI systems are entering critical domains like healthcare, finance, and defense, yet remain vulnerable to adversarial attacks. While AI red teaming is a

Reduced-order Neural Modeling with Differentiable Simulation for High-Detail Tactile Perception

arXiv:2605.05053v1 Announce Type: cross Abstract: Tactile perception is key to dexterous manipulation, yet simulating high-resolution elastomer deformation remains computationally prohibitive. Finite

RemoteZero: Geospatial Reasoning with Zero Human Annotations

arXiv:2605.04451v1 Announce Type: new Abstract: Geospatial reasoning requires models to resolve complex spatial semantics and user intent into precise target locations for Earth observation. Recent pr

agentsarxiv-cs-cv

Robust Agent Compensation (RAC): Teaching AI Agents to Compensate

arXiv:2605.03409v1 Announce Type: new Abstract: We present Robust Agent Compensation (RAC), a log-based recovery paradigm (providing a safety net) implemented through an architectural extension that c

SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models

arXiv:2601.08623v2 Announce Type: replace Abstract: Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from

safetyarxiv-cs-cv

Scalable inference of spatial regions and temporal signatures from time series

arXiv:2605.05008v1 Announce Type: cross Abstract: Regionalization aims to partition a spatial domain into contiguous regions that share similar characteristics, enabling more effective spatial analysi

safetyarxiv-cs-lg