Search: “models”

Seeing Through the Weights: Privacy Leakage in Scene Coordinate Regression

arXiv:2606.31164v1 Announce Type: new Abstract: Scene Coordinate Regression (SCR) methods are increasingly adopted for visual localization. In these approaches, the scene is implicitly encoded within

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Hardware

SeKV: Resolution-Adaptive KV Cache with Hierarchical Semantic Memory for Long-Context LLM Inference

DGX agent

arXiv:2606.31145v1 Announce Type: new Abstract: Large language models increasingly operate over long contexts, where the KV cache becomes a dominant memory bottleneck: its size grows linearly with seq

hardwarearxiv-cs-cl

1 Jul 2026

SpectralSplats: Robust Differentiable Tracking via Spectral Moment Supervision

arXiv:2603.24036v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) enables real-time, photorealistic novel view synthesis, making it a highly attractive representation for model-based vi

safetyarxiv-cs-cv

SpheRoPE: Zero-Shot Optimization-Free 360 Panorama Generation with Spherical RoPE

arXiv:2606.32033v1 Announce Type: new Abstract: We present a zero-shot, training-free and optimization-free framework for generating 360 panoramic images and videos by directly injecting spherical pri

Surprise as a Signal for Plasticity and Metacognition

arXiv:2606.31495v1 Announce Type: new Abstract: We study a single idea across two settings: that a prediction-error signal, computed by a small predictor over the latent space of a frozen encoder, can

Technical Report of RoboSpatial Challenge at CVPR 2026: Selective Reasoning Activation and Reference-Frame Disambiguation for Embodied Spatial Reasoning

arXiv:2606.31645v1 Announce Type: new Abstract: Vision-language models achieve strong general perception but often struggle with the spatial reasoning required for embodied tasks. We present RoboSpati

The HydroGym Reinforcement Learning Platform for Fluid Dynamics

arXiv:2512.17534v2 Announce Type: replace-cross Abstract: Modeling and controlling fluids is critical across science and engineering. Effective flow control can increase lift, reduce drag, enhance mix

Think While You Map: Asynchronous Vision-Language Agents for Incremental 3D Scene Graphs

arXiv:2606.31471v1 Announce Type: new Abstract: Open-vocabulary 3D scene graph methods typically operate in two stages: first reconstruct, then enrich with vision-language models, leaving the graph un

Hardware

Together AI raises $800M to grow its AI-optimized public cloud

Together AI Inc., the operator of a cloud platform optimized to run open-source artificial intelligence models, has raised 800 million from investors. The startup stated in its funding announcement to

hardwaresiliconangle

Training Therapeutic Judges and Multi-Agent Systems for Human-Aligned Mental Health Support

arXiv:2606.30887v1 Announce Type: cross Abstract: Large language models show promise for mental health support, yet therapeutic quality improves only when evaluation functions as an actionable control

VS3R: Robust Full-frame Video Stabilization via Deep 3D Reconstruction

arXiv:2603.05851v2 Announce Type: replace Abstract: Video stabilization aims to mitigate camera shake but faces a fundamental trade-off between geometric robustness and full-frame consistency. While 2

WarpHammer: Densifying Scene Warps with 3D Object Priors for Extreme View Synthesis

arXiv:2606.31258v1 Announce Type: new Abstract: Projection-conditioned novel view synthesis (NVS) warps an explicit 3D reconstruction of the input view into the target camera and conditions a generato

WaterGen: Decoupling Scene and Medium in Underwater Image Generation

arXiv:2606.31147v1 Announce Type: new Abstract: Underwater computer vision tasks, such as detection, restoration, and segmentation, are limited by the scarcity of large-scale and diverse training data

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP

arXiv:2606.30342v1 Announce Type: new Abstract: Adversarial attacks pose a challenge to the reliability of deep learning models, motivating effective detection methods. Existing techniques often rely

A Dual-domain Refinement Network with FBP-based Jacobian Learning for Sparse-view Dual-Energy CT Material Decomposition

arXiv:2606.30159v1 Announce Type: new Abstract: Dual-energy CT (DECT) exploits attenuation differences across different X-ray spectra to provide richer material information and has been widely used in

A Knowledge Theory of Capital:The Value of Natural and Artificial Intelligence, Volume 1

arXiv:2606.18288v2 Announce Type: replace-cross Abstract: This volume develops a knowledge theory of capital for economies in which productive capacity increasingly resides in software, data, models,

applicationsarxiv-cs-ai

A Multi-task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution

arXiv:2606.30572v1 Announce Type: cross Abstract: Malware classification remains a challenging problem due to its inherent heterogeneity, the presence of packed binaries, and the diverse distribution

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation

arXiv:2606.28896v1 Announce Type: cross Abstract: Synthetic aperture radar (SAR) data augmentation is important for improving the generalization of data-driven SAR interpretation models, yet practical

'AI Watermarking': Bridging Policy Discourse and Technical Capabilities

arXiv:2606.28331v1 Announce Type: cross Abstract: The widespread deployment of generative artificial intelligence (AI) models has raised serious concerns about the proliferation of AI-generated conten

ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data

arXiv:2408.16028v4 Announce Type: replace-cross Abstract: Supervised-learning-based vulnerability detectors often fall short due to limited labelled training data. In contrast, Large Language Models (

researcharxiv-cs-lg

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms

arXiv:2606.30577v1 Announce Type: new Abstract: We present APRIL-MedSeg, a YAML-driven modular framework for 2D medical image segmentation. It provides a unified and extensible ecosystem that decompos

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization

arXiv:2510.06732v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small,

Local Ai

Aristotelian Virtue Profiling of LLMs through Ethical Dilemmas

arXiv:2606.28683v1 Announce Type: new Abstract: Large Language Models (LLMs) often face ethical tradeoffs in which several responses may be defensible but express different priorities, such as fairnes

local-aiarxiv-cs-ai

Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems

arXiv:2510.20640v2 Announce Type: replace Abstract: In this paper, we present DiRecGNN, an attention-enhanced entity recommendation framework for monitoring cloud services at Microsoft. We provide ins

applicationsarxiv-cs-lg

Local Ai

b9850

local-aillama-cpp-releases

Release b9850 is a version of llama.cpp, an open-source software library for large language model inference developed alongside the GGML tensor library. This release likely includes updates, bug fixes

BayesEvolve: Explicit Belief States for Autonomous Scientific Discovery

arXiv:2606.30335v1 Announce Type: new Abstract: Autonomous scientific discovery systems increasingly use large language models (LLMs) to propose new hypotheses, but many such systems condition primari

Local Ai

Beyond 2D Matching: A Unified Single-Stage Framework for Geometry-Aware Cross-View Object Geo-Localization

arXiv:2606.30576v1 Announce Type: cross Abstract: Cross-view object geo-localization (CVOGL) aims to locate a target object from a query view (e.g., ground or drone) within a geo-tagged reference imag

local-aiarxiv-cs-ai

Beyond Spectral Decomposition: Bayesian Contrastive Learning and its Non-negative Formulation via Factor Analysis

arXiv:2407.21740v3 Announce Type: replace-cross Abstract: Factor analysis, often regarded as a Bayesian variant of matrix factorization, offers superior capabilities in capturing uncertainty, modeling

CAPTCHA Solving for Native GUI Agents: Automated Reasoning-Action Data Generation and Self-Corrective Training

arXiv:2603.23559v2 Announce Type: replace-cross Abstract: GUI agents are rapidly shifting from multi-module pipelines to end-to-end, native vision-language models (VLMs) that perceive raw screenshots

Categorize Early, Integrate Late: Divergent Processing Strategies in Automatic Speech Recognition

arXiv:2601.06972v2 Announce Type: replace Abstract: In speech language modeling, two architectures dominate the frontier: the Transformer and the Conformer. However, it remains unknown whether their c

researcharxiv-cs-cl

Character Recognition of Nepali Number Plate

arXiv:2606.28946v1 Announce Type: new Abstract: This paper presents a robust Automatic Number Plate Recognition (ANPR) system tailored for Nepali license plates written in Devanagari script. In this p

applicationsarxiv-cs-cv

CLARity: Reasoning Consistency Alone Can Teach Reinforced Experts

arXiv:2510.09278v2 Announce Type: replace-cross Abstract: Training expert LLMs in domains with scarce data is difficult, often relying on multiple-choice questions (MCQs). However, standard outcome-ba

Hardware

CLEAR-MoE: Shared-Basis Expert Extraction from Frozen Vision Transformers via Calibration-Driven Layer Selection

arXiv:2606.28516v1 Announce Type: new Abstract: We present CLEAR-MoE, a four-phase post-training pipeline that converts a frozen pretrained Vision Transformer (ViT) into a sparse Mixture-of-Experts (M

hardwarearxiv-cs-cv

Clinical Risk-Aware Multi-Level Grading for Coronary Artery Stenosis through Curved Feature Reconstruction

arXiv:2606.30082v1 Announce Type: new Abstract: Developing a multi-level grading model for coronary artery stenosis holds great clinical significance for the diagnosis of coronary artery disease. Howe

Correct codes for the wrong reasons? validating LLMs as measurement instruments for theoretical constructs

arXiv:2606.28574v1 Announce Type: cross Abstract: When a large language model (LLM) codes a construct in text as a human annotator would, that agreement makes the LLM a reliable coder. Yet reliability

Cybersecurity is the True Frontier for Generative AI Success or Failure

arXiv:2606.28929v1 Announce Type: cross Abstract: Cybersecurity is a real-life test-bed for many machine learning problems at once, especially when considering modern strides in using Large Language M

researcharxiv-cs-lg

CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training

arXiv:2601.12282v2 Announce Type: replace-cross Abstract: The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial a

D^{2}R^{2}OSR: Degradation-Disentangled Representation for Real-World Omnidirectional Image Super-Resolution

arXiv:2606.29314v1 Announce Type: new Abstract: With the growing demand for immersive visual experiences, high-quality omnidirectional images (ODIs) have become increasingly important. However, limita

applicationsarxiv-cs-cv

Deterministic Decisions for High-Stakes AI. A Zero-Egress Pipeline with the Deployability of RAG and the Accuracy of Machine Learning

arXiv:2606.29280v1 Announce Type: cross Abstract: We identify intervention bias as a previously unquantified failure mode of zero-shot large-language-model (LLM) educational advisory agents: without t

Diff-MN: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations

arXiv:2601.13534v3 Announce Type: replace-cross Abstract: Time series generation (TSG) is widely used across domains, yet most existing methods assume regular sampling and fixed output resolutions. Th

DTI: Dynamic Trajectory Initialization for Generative Face Video Super-Resolution

arXiv:2606.29198v1 Announce Type: new Abstract: As the most perceptually powerful Face Video Super-Resolution (FVSR) method, existing works in Generative FVSR (GFVSR) mainly exploit the generative pri

safetyarxiv-cs-cv

EfficientUICoder: A Bidirectional Token Compression Framework for Efficient MLLM-Based UI Code Generation

arXiv:2509.12159v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models have demonstrated exceptional performance in UI2Code tasks, significantly enhancing website development effic

Enhancing Part-Level Point Grounding for Any Open-Source MLLMs

arXiv:2606.29267v1 Announce Type: new Abstract: Visual grounding aims to associate free-form textual queries with specific regions in an image. While recent Multimodal Large Language Models (MLLMs) ha

EraseLoRA: MLLM-Driven Foreground Exclusion and Background Subtype Aggregation for Dataset-Free Object Removal

arXiv:2512.21545v2 Announce Type: replace Abstract: Object removal must prevent the masked target from reappearing and reconstruct the occluded background with structural and contextual fidelity, rath

safetyarxiv-cs-cv

Estimating Grammatical Gender Directions in Contextual Embeddings under Controlled and Natural Contexts

arXiv:2606.30152v1 Announce Type: cross Abstract: Contextual language models conflate grammatical gender and social semantic bias in gendered languages such as Spanish. Existing gender debiasing appro

Evaluating LLMs on Chinese Topic Constructions: A Research Proposal Inspired by Tian et al. (2024)

arXiv:2504.14969v2 Announce Type: replace Abstract: This paper proposes a framework for evaluating large language models (LLMs) on Chinese topic constructions, focusing on their sensitivity to island

researcharxiv-cs-cl

Evidence-Driven LLM Agent for C-to-Synthesizable-C Conversion and Verification

arXiv:2606.28409v1 Announce Type: cross Abstract: Software-compilable C programs routinely fail to complete the four-stage pipeline of a high-level synthesis (HLS) toolchain -- compilation, C simulati

Evidence-Informed LLM Beliefs for Continual Scientific Discovery

arXiv:2606.29182v1 Announce Type: new Abstract: Open-ended scientific discovery with large language models (LLMs) increasingly operates as a long-horizon loop of hypothesis search and verification, wh