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Rethinking Multi-Branch and Cross-Backbone Fusion for Vehicle Re-Identification in the Foundation-Model Era

arXiv:2607.22068v1 Announce Type: new Abstract: Multi-branch architectures and CNN-Transformer fusion have long been regarded as effective ways to improve vehicle re-identification (Re-ID) by combinin

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Hardware

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention

DGX agent

arXiv:2607.21927v1 Announce Type: new Abstract: Full self-attention in large language models scales as O(N^2), which limits long-context document analysis to 65,536 tokens and requires costly GPU clus

hardwarearxiv-cs-lg

27 Jul 2026

Risk-Routed Implicit Boundary Refinement for Robust Ultrasound Image Segmentation

arXiv:2607.21787v1 Announce Type: new Abstract: Medical ultrasound (US) image segmentation faces significant challenges due to speckle noise, low-contrast boundaries, acoustic shadowing, and acquisiti

Tutorials

Robot-Factored World Models via Robot Rendering

arXiv:2607.22535v1 Announce Type: cross Abstract: Action-conditioned video world models predict future observations from an initial observation and an action signal. In robotics, actions influence fut

tutorialsarxiv-cs-cv

Robot Learning to Communicate through Projected Visual Abstractions

arXiv:2607.22434v1 Announce Type: new Abstract: Humans routinely communicate through abstractions of their bodies, including shadows, silhouettes, and reflections. Yet robots remain largely confined t

researcharxiv-cs-ro

Safe Learning Predictive Control for Ego-World Robotic Systems

arXiv:2607.22225v1 Announce Type: new Abstract: Safe autonomous navigation in shared environments requires the ability to anticipate and react to the latent behaviors of surrounding robots. In this pa

safetyarxiv-cs-ro

Local Ai

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes

arXiv:2607.21850v1 Announce Type: new Abstract: As semiconductor manufacturing advances toward sub-2nm nodes, local place-and-route (P&R) design-rule violation (DRV) fixing is increasingly limited by

local-aiarxiv-cs-cv

Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study

arXiv:2607.21866v1 Announce Type: new Abstract: Prior classical-ML learning-curve work fits power laws to tree, linear, and kernel models on tabular data, but at small scale: typically one curve, one

Scaling Native Multimodal Pre-Training From Scratch

arXiv:2607.22043v1 Announce Type: new Abstract: Although large language models (LLMs) exhibit remarkable reasoning capabilities, their reliance on text-only pre-training restricts the perception of th

researcharxiv-cs-cl

SceneActBench: Can Agents Act on the 3D Scenes They See?

arXiv:2607.22393v1 Announce Type: cross Abstract: Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existing 3D benchmarks score textual res

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text

arXiv:2607.21610v1 Announce Type: cross Abstract: Schema graphs are an upstream bottleneck of schema-grounded information extraction and knowledge graph construction, yet most extraction systems assum

Searching the Space of Feed-Forward Neural-Network Weight-Update Rules with Fixed Depth Symbolic Regression

arXiv:2607.21855v1 Announce Type: new Abstract: We investigate whether symbolic regression can discover explicit neural network weight-update rules that outperform standard hand-designed optimizers on

Security Without Detection: Economic Denial as a Primitive for Edge and IoT Defense

arXiv:2512.23849v2 Announce Type: replace-cross Abstract: Sophisticated attackers can evade detection-based security by using encryption, stealth tactics, and low-rate attack patterns. This challenge

safetyarxiv-cs-lg

Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning

arXiv:2507.01551v3 Announce Type: replace-cross Abstract: Process Reinforcement Learning~(PRL) has demonstrated considerable potential in enhancing the reasoning capabilities of Large Language Models~

safetyarxiv-cs-cl

Self-Poisoning in Adaptive Out-of-Distribution Detection: A Sharp-Threshold Theory and Certified Label-Free Calibration

arXiv:2607.21673v1 Announce Type: cross Abstract: Test-time adaptive out-of-distribution (OOD) detectors update a memory bank from the unlabelled stream. We show this adaptation obeys a provable dynam

Shallower ReLU Network Representations via Exact Linear Algebra

arXiv:2607.21651v1 Announce Type: new Abstract: We prove that the maximum of n real numbers is exactly representable by a ReLU network with two hidden layers for every nle 10. The constructions are ob

Simulation-Based Empirical Bayes

arXiv:2607.21843v1 Announce Type: cross Abstract: Empirical Bayes (EB) performs simultaneous inference across many related latent variables. Classical EB assumes that the likelihood p(x | z) is tracta

applicationsarxiv-cs-lg

Hardware

Singular value soft-thresholding via the polar decomposition

arXiv:2607.22484v1 Announce Type: cross Abstract: Singular value soft-thresholding can be computed via a reduction to the matrix polar decomposition, which allows one to exploit GPU-friendly algorithm

hardwarearxiv-cs-lg

SiPhy: Single-Image Physical Property Reasoning

arXiv:2607.22355v1 Announce Type: new Abstract: Inferring physical properties such as mass, stiffness, and elasticity from a single image is essential for simulation and embodied AI, yet most existing

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills

model-releasesarxiv-cs-cl

arXiv:2607.22529v1 Announce Type: new Abstract: LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing self-evolutionary methods face a fund

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images

arXiv:2607.22332v1 Announce Type: new Abstract: Interactive deep image segmentation enables efficient medical image annotation by iteratively refining predictions from user prompts, such as positive a

SM4RT: Learning Structured Motion Geometry for 4D Reconstruction

arXiv:2607.22534v1 Announce Type: new Abstract: Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capability to 4D dynamic understanding rem

applicationsarxiv-cs-cv

Small Vision-Language Models Know When They Are Wrong But Cannot Say So: A Two-Model Study of Stated versus Internal Confidence Under Realistic Image Degradation

arXiv:2607.22034v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed on consumer hardware where input images are degraded by compression, camera shake, and poor li

researcharxiv-cs-cl

Smart predict-then-robustly-optimize

arXiv:2607.21773v1 Announce Type: new Abstract: In this paper, we propose and study a robust variant of the smart predict-then-optimize approach that accounts for prediction shifts due to disturbance

Spatially-Enhanced Temporal Fusion Transformer: Interpretable Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs

arXiv:2505.00473v2 Announce Type: replace Abstract: We explore the promising performance of a transformer model in predicting outputs of parametric dynamical systems with external time-varying input s

Spectral Flow Certificates for Depth-Aware Long-Range Propagation in Graph Neural Networks

arXiv:2607.21607v1 Announce Type: cross Abstract: Graph Neural Networks propagate information through local message passing, but the graph topologies themselves can silently prevent any amount of trai

Spectral Prior for Reducing Exposure Bias in Diffusion Models

arXiv:2607.22091v1 Announce Type: new Abstract: Diffusion models typically suffer from error accumulation during iterative sampling, commonly referred to as exposure bias. We reveal systematic frequen

safetyarxiv-cs-cv

StARS: Socially Appropriate Robot Actions via a Recommender System-Driven Approach

arXiv:2607.21802v1 Announce Type: new Abstract: Social appropriateness in human-robot interaction (HRI) is not universal: different people can judge the same robot action differently in the same situa

researcharxiv-cs-ro

Tutorials

Statistical mechanics of extensive-width Bayesian neural networks near interpolation

arXiv:2505.24849v2 Announce Type: replace-cross Abstract: For three decades statistical mechanics has been providing a framework to analyse neural networks. However, the theoretically tractable models

tutorialsarxiv-cs-lg

Stop to Decide: Latency-Aware Proprioceptive Navigation Primitives for Mapping-Free Quadruped Inspection

model-releasesarxiv-cs-ro

arXiv:2607.11204v2 Announce Type: replace Abstract: Onboard quadruped inspection systems often share limited compute between perception and navigation, reducing the rate at which event-triggered contr

SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis

arXiv:2509.22352v3 Announce Type: replace Abstract: Survival analysis is a cornerstone of clinical research by modeling time-to-event outcomes such as metastasis, disease relapse, or patient death. Un

Susceptible Reservoir Architectures for Regime-Conditional Volatility Forecasting

arXiv:2607.22491v1 Announce Type: new Abstract: Volatility forecasting is dominated by persistence and measurement noise, leaving limited residual structure for nonlinear models to exploit. We introdu

SwiftMem: Fast Agentic Memory via Query-aware Indexing

model-releasesarxiv-cs-cl

arXiv:2601.08160v2 Announce Type: replace Abstract: Agentic memory systems have become critical for enabling LLM agents to maintain long-term context and retrieve relevant information efficiently. How

Synthetic Speech, Real Signal: Paralinguistic Preservation and Cross-Lingual Augmentation via Voice Cloning

arXiv:2607.22304v1 Announce Type: new Abstract: Synthetic data augmentation in speech is common practice for linguistic tasks like ASR, but has seen far less work for paralinguistic ones, especially c

TDiR: Transformer based Diffusion for Image Restoration Tasks

arXiv:2506.20302v2 Announce Type: replace Abstract: Images captured in challenging environments often experience various types of degradation, such as noise, color cast, blur, and light scattering. Th

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning

arXiv:2607.21971v1 Announce Type: cross Abstract: Test-time scaling through iterative self-evolution with environment feedback, as demonstrated by AlphaEvolve, shows remarkable performance gains. We h

researcharxiv-cs-cl

Teachy Mini: Development and Preliminary Evaluation of a Knowledge-Based Generative Social Robot for Higher Education

arXiv:2607.22345v1 Announce Type: new Abstract: Generative social robots (GSRs) powered by large language models offer new possibilities for personalized tutoring in higher education, but also introdu

applicationsarxiv-cs-ro

TextSLIP: Text Self-Supervised CLIP for Medical Report Generation

arXiv:2607.21970v1 Announce Type: new Abstract: Automating radiology report generation is important for improving reporting consistency and clinical workflows . While Contrastive Language--Image Pretr

safetyarxiv-cs-cv

The 3D Mirage: Probing and Taming 3D Hallucinations

arXiv:2512.15423v2 Announce Type: replace Abstract: Monocular depth foundation models achieve remarkable generalization by learning large-scale semantic priors, but this creates a critical vulnerabili

The Coordination Gap: Multi-Agent Alternation Metrics for Temporal Fairness in Repeated Games

arXiv:2603.05789v5 Announce Type: replace-cross Abstract: Repeated multi-agent interactions require evaluation metrics that capture not only payoff distributions but also their temporal organization.

safetyarxiv-cs-lg

The Hard Decision Layer: Evidence for Committed Inference in Transformers

model-releasesarxiv-cs-cl

arXiv:2607.21613v1 Announce Type: cross Abstract: We investigate where and how transformer-based language models commit to predictions in multiple-choice question answering. We identify the _Hard Deci

The Lift Spectrum: How Measurement-to-Space Adaptivity Shapes Robustness in Image-Free Single-Pixel Sensing

arXiv:2607.22077v1 Announce Type: cross Abstract: Single-pixel sensing encodes a scene as a short sequence of coded measurements, and image-free methods infer the task directly from that sequence. Rem

Local Ai

The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis

arXiv:2601.19618v2 Announce Type: replace Abstract: Differential privacy protects the patients whose images train medical imaging models, but it lowers diagnostic accuracy, and the initialization is t

local-aiarxiv-cs-cv

The Role of Pseudo-labels in Self-training Linear Classifiers on High-dimensional Gaussian Mixture Data

arXiv:2205.07739v4 Announce Type: replace-cross Abstract: Self-training (ST) is a simple yet effective semi-supervised learning method. However, why and how ST improves generalization performance by u

Time-Reversed Imaging: A Multimodal Benchmark and Framework for Reconstructing Past Human-Environment Interactions

arXiv:2607.22352v1 Announce Type: new Abstract: We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces. Instead of extrapolating or

Token-Operations-Oriented Inference Optimization Techniques for Large Models

arXiv:2606.20295v2 Announce Type: replace-cross Abstract: Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large mode

applicationsarxiv-cs-cl

Toward Goal-Agnostic Joint-Embedding Predictive Control of Partial Differential Equations

arXiv:2607.21644v1 Announce Type: new Abstract: We present a goal-agnostic control framework for partial differential equations (PDEs) built around a joint-embedding predictive architecture (JEPA). Th

Local Ai

Toward High-Fidelity 3D Point-Cloud Learning for Brain Folding Morphology Prediction Using Trans-Unet

arXiv:2607.21840v1 Announce Type: new Abstract: Learning high-fidelity point-cloud features in the 3D space poses significant challenges, including permutation invariance, lack of local context, diffi

local-aiarxiv-cs-cv