Search: “framework”

OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion

arXiv:2604.12356v1 Announce Type: new Abstract: Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datase

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Model Releases

On Higher-Order Geometric Refinements of Classical Covariance Asymptotics: An Approach via Intrinsic and Extrinsic Information Geometry

DGX agent

arXiv:2604.12725v1 Announce Type: cross Abstract: Classical Fisher-information asymptotics describe the covariance of regular efficient estimators through the local quadratic approximation of the log-

model-releasesarxiv-cs-lg

15 Apr 2026

On the Geometry of Receiver Operating Characteristic and Precision-Recall Curves

arXiv:2504.02169v3 Announce Type: replace-cross Abstract: We study the geometry of Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves in binary classification problems. The key f

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy

researcharxiv-cs-ai

PAL: Personal Adaptive Learner

arXiv:2604.13017v1 Announce Type: new Abstract: AI-driven education platforms have made some progress in personalisation, yet most remain constrained to static adaptation--predefined quizzes, uniform

PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning

arXiv:2604.12100v1 Announce Type: new Abstract: Whole-slide image (WSI) classification in computational pathology is commonly formulated as slide-level Multiple Instance Learning (MIL) with a single g

local-aiarxiv-cs-cv

Perception-Aware Policy Optimization for Multimodal Reasoning

arXiv:2507.06448v5 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has proven to be a highly effective strategy for endowing Large Language Models (LLMs) with ro

safetyarxiv-cs-cl

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography

arXiv:2604.12239v1 Announce Type: new Abstract: Accurate inter-vehicle distance estimation is a cornerstone of Advanced Driver Assistance Systems (ADAS) and autonomous driving. While LiDAR and radar p

safetyarxiv-cs-cv

Pi-HOC: Pairwise 3D Human-Object Contact Estimation

arXiv:2604.12923v1 Announce Type: new Abstract: Resolving real-world human-object interactions in images is a many-to-many challenge, in which disentangling fine-grained concurrent physical contact is

applicationsarxiv-cs-cv

PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination

arXiv:2604.12856v1 Announce Type: new Abstract: Audio-driven bimanual piano motion generation requires precise modeling of complex musical structures and dynamic cross-hand coordination. However, exis

PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models

arXiv:2601.19917v2 Announce Type: replace Abstract: Strategic planning is critical for multi-step reasoning, yet compact Large Language Models (LLMs) often lack the capacity to formulate global strate

researcharxiv-cs-cl

Policy-Invisible Violations in LLM-Based Agents

arXiv:2604.12177v1 Announce Type: new Abstract: LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational polic

Privacy-Preserving Transfer Learning for Community Detection using Locally Distributed Multiple Networks

arXiv:2504.00890v2 Announce Type: replace-cross Abstract: Modern applications increasingly involve highly sensitive network data, where raw edges cannot be shared due to privacy constraints. We propos

researcharxiv-cs-lg

Progress-Think: Semantic Progress Reasoning for Vision-Language Navigation

arXiv:2511.17097v2 Announce Type: replace Abstract: Vision-Language Navigation requires agents to act coherently over long horizons by understanding not only local visual context but also how far they

safetyarxiv-cs-ro

PubSwap: Public-Data Off-Policy Coordination for Federated RLVR

arXiv:2604.12160v1 Announce Type: new Abstract: Reasoning post-training with reinforcement learning from verifiable rewards (RLVR) is typically studied in centralized settings, yet many realistic appl

safetyarxiv-cs-lg

Qwen3 technical arch

local-air-stablediffusion

Qwen3 is a series of large language models spanning both dense and Mixture-of-Experts (MoE) architectures, with parameter scales ranging from 0.6B to 235B, and a key innovation being the integration o

Agents

Radar-Camera BEV Multi-Task Learning with Cross-Task Attention Bridge for Joint 3D Detection and Segmentation

arXiv:2604.12918v1 Announce Type: new Abstract: Bird's-eye-view (BEV) representations are the dominant paradigm for 3D perception in autonomous driving, providing a unified spatial canvas where detect

agentsarxiv-cs-cv

RankOOD -- Class Ranking-based Out-of-Distribution Detection

model-releasesarxiv-cs-lg

arXiv:2511.19996v2 Announce Type: replace Abstract: We propose RankOOD, a rank-based Out-of-Distribution (OOD) detection approach based on training a model with the Placket-Luce loss, which is now ext

Redefining Quality Criteria and Distance-Aware Score Modeling for Image Editing Assessment

arXiv:2604.12175v1 Announce Type: new Abstract: Recent advances in image editing have heightened the need for reliable Image Editing Quality Assessment (IEQA). Unlike traditional methods, IEQA require

safetyarxiv-cs-cv

ReefMapGS: Enabling Large-Scale Underwater Reconstruction by Closing the Loop Between Multimodal SLAM and Gaussian Splatting

arXiv:2604.11992v1 Announce Type: cross Abstract: 3D Gaussian Splatting is a powerful visual representation, providing high-quality and efficient 3D scene reconstruction, but it is crucially dependent

RegD: Hierarchical Embeddings via Dissimilarity between Arbitrary Euclidean Regions

arXiv:2501.17518v3 Announce Type: replace-cross Abstract: Hierarchical data is common in many domains like life sciences and e-commerce, and its embeddings often play a critical role. While hyperbolic

Representation geometry shapes task performance in vision-language modeling for CT enterography

arXiv:2604.13021v1 Announce Type: cross Abstract: Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices t

researcharxiv-cs-ai

Rethinking Satellite Image Restoration for Onboard AI: A Lightweight Learning-Based Approach

arXiv:2604.12807v1 Announce Type: cross Abstract: Satellite image restoration aims to improve image quality by compensating for degradations (e.g., noise and blur) introduced by the imaging system and

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation

arXiv:2604.12219v1 Announce Type: cross Abstract: Video Diffusion Transformers have revolutionized high-fidelity video generation but suffer from the massive computational burden of self-attention. Wh

local-aiarxiv-cs-ai

RMGS-SLAM: Real-time Multi-sensor Gaussian Splatting SLAM

arXiv:2604.12942v1 Announce Type: new Abstract: Real-time 3D Gaussian splatting (3DGS)-based Simultaneous Localization and Mapping (SLAM) in large-scale real-world environments remains challenging, as

applicationsarxiv-cs-ro

Robust Explanations for User Trust in Enterprise NLP Systems

arXiv:2604.12069v1 Announce Type: cross Abstract: Robust explanations are increasingly required for user trust in enterprise NLP, yet pre-deployment validation is difficult in the common case of black

Robust Federated Inference

arXiv:2510.00310v3 Announce Type: replace Abstract: Federated inference, in the form of one-shot federated learning, edge ensembles, or federated ensembles, has emerged as an attractive solution to co

local-aiarxiv-cs-lg

RoleMAG: Learning Neighbor Roles in Multimodal Graphs

arXiv:2604.12271v1 Announce Type: new Abstract: Multimodal attributed graphs (MAGs) combine multimodal node attributes with structured relations. However, existing methods usually perform shared messa

researcharxiv-cs-lg

RPG-SAM: Reliability-Weighted Prototypes and Geometric Adaptive Threshold Selection for Training-Free One-Shot Polyp Segmentation

model-releasesarxiv-cs-cv

arXiv:2603.07436v2 Announce Type: replace Abstract: Training-free one-shot segmentation offers a scalable alternative to expert annotations where knowledge is often transferred from support images and

Safe-FedLLM: Delving into the Safety of Federated Large Language Models

arXiv:2601.07177v2 Announce Type: replace-cross Abstract: Federated learning (FL) addresses privacy and data-silo issues in the training of large language models (LLMs). Most prior work focuses on imp

local-aiarxiv-cs-ai

SAM3-I: Segment Anything with Instructions

arXiv:2512.04585v3 Announce Type: replace Abstract: Segment Anything Model 3 (SAM3) advances open-vocabulary segmentation through promptable concept segmentation, enabling users to segment all instanc

safetyarxiv-cs-cv

Hardware

Scalable Trajectory Generation for Whole-Body Mobile Manipulation

arXiv:2604.12565v1 Announce Type: cross Abstract: Robots deployed in unstructured environments must coordinate whole-body motion -- simultaneously moving a mobile base and arm -- to interact with the

hardwarearxiv-cs-cv

Scalable Verification of Neural Control Barrier Functions Using Linear Bound Propagation

arXiv:2511.06341v2 Announce Type: replace Abstract: Control barrier functions (CBFs) are a popular tool for safety certification of nonlinear dynamical control systems. Recently, CBFs represented as n

safetyarxiv-cs-lg

Scaling Exposes the Trigger: Input-Level Backdoor Detection in Text-to-Image Diffusion Models via Cross-Attention Scaling

arXiv:2604.12446v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models have achieved remarkable success in image synthesis, but their reliance on large-scale data and open ecosystems i

Schema-Adaptive Tabular Representation Learning with LLMs for Generalizable Multimodal Clinical Reasoning

arXiv:2604.11835v1 Announce Type: cross Abstract: Machine learning for tabular data remains constrained by poor schema generalization, a challenge rooted in the lack of semantic understanding of struc

safetyarxiv-cs-ai

Tutorials

SDFed: Bridging Local Global Discrepancy via Subspace Refinement and Divergence Control in Federated Prompt Learning

arXiv:2602.08590v4 Announce Type: replace Abstract: Vision-language pretrained models offer strong transferable representations, yet adapting them in privacy-sensitive multi-party settings is challeng

tutorialsarxiv-cs-lg

Hardware

Security Researchers - Get Rewarded for Bug Reports!

Discover how Vultr values and rewards the ethical disclosure of security vulnerabilities with its new bug bounty program. Report issues, get compensated, and help improve Vultr's web ecosystem through

hardwarevultr

Self-Adversarial One Step Generation via Condition Shifting

model-releasesarxiv-cs-cv

arXiv:2604.12322v1 Announce Type: new Abstract: The push for efficient text to image synthesis has moved the field toward one step sampling, yet existing methods still face a three way tradeoff among

SEW: Self-Evolving Agentic Workflows for Automated Code Generation

arXiv:2505.18646v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated effectiveness in code generation tasks. To enable LLMs to address more complex coding challenge

Tutorials

Siamese Foundation Models for Crystal Structure Prediction

arXiv:2503.10471v2 Announce Type: replace-cross Abstract: Predicting crystal structures from chemical compositions is a fundamental challenge in materials discovery, complicated by complex 3D geometri

tutorialsarxiv-cs-ai

SIR-Bench: Evaluating Investigation Depth in Security Incident Response Agents

arXiv:2604.12040v1 Announce Type: cross Abstract: We present SIR-Bench, a benchmark of 794 test cases for evaluating autonomous security incident response agents that distinguishes genuine forensic in

Tutorials

Social Learning Strategies for Evolved Virtual Soft Robots

arXiv:2604.12482v1 Announce Type: cross Abstract: Optimizing the body and brain of a robot is a coupled challenge: the morphology determines what control strategies are effective, while the control pa

tutorialsarxiv-cs-ai

SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling

arXiv:2604.12110v1 Announce Type: new Abstract: Recent advances in recommendation scaling laws have led to foundation models of unprecedented complexity. While these models offer superior performance,

researcharxiv-cs-lg

Agents

SolarWinds accelerates observability with SW1, an ‘agentic AI teammate’ that automates IT firefighting

SolarWinds Worldwide LLC is making its play for the future of autonomous information technology operations with the launch of a new “agentic AI teammate” called SW1. Available starting today, it’s des

agentssiliconangle

Sparse Growing Transformer: Training-Time Sparse Depth Allocation via Progressive Attention Looping

model-releasesarxiv-cs-cl

arXiv:2603.23998v2 Announce Type: replace Abstract: Existing approaches to increasing the effective depth of Transformers predominantly rely on parameter reuse, extending computation through recursive

Speaker effects in language comprehension: An integrative model of language and speaker processing

arXiv:2412.07238v3 Announce Type: replace Abstract: The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and

researcharxiv-cs-cl

SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration

arXiv:2604.12247v1 Announce Type: cross Abstract: Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, w

researcharxiv-cs-ai

SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism

arXiv:2506.01979v4 Announce Type: replace-cross Abstract: Recently, speculative decoding (SD) has emerged as a promising technique to accelerate LLM inference by employing a small draft model to propo