Search: “papers”

arXiv:2510.13310v3 Announce Type: replace Abstract: Structure-from-Motion (SfM) is a fundamental technique for recovering camera poses and scene structure from multi-view imagery, serving as a critica

hardwarearxiv-cs-cv

Integrity of peer-to-peer distributed LLM inference under malicious nodes

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DGX agent

arXiv:2607.19490v1 Announce Type: cross Abstract: Peer-to-peer distributed inference executes a Large Language Model (LLM) on pooled consumer hardware by spreading its layers across many nodes. Every

researcharxiv-cs-ai

23 Jul 2026

Interpretable Fuzzy Rule-Based Regression Extension for Ex-Fuzzy Library

arXiv:2607.20277v1 Announce Type: new Abstract: Machine learning models achieve high predictive accuracy in regression tasks, but their deployment in safety-critical and regulated domains requires int

Language-Specific versus Cross-Lingual Knowledge Graphs for Implicit Aspect Identification in Arabic: A Comparative Study of Reasoning and Adaptation Strategies

arXiv:2607.20056v1 Announce Type: cross Abstract: Aspect-based sentiment analysis (ABSA) in Arabic must recover both explicitly stated aspects and implicit aspects that are never named in the text. Im

Tutorials

Learning Semantic-Robust Change Detection via Semantic-Invariant Self-Distillation

arXiv:2607.19000v1 Announce Type: new Abstract: Change detection aims to identify semantic changes between remote sensing images. However, features from models are easily disturbed by non-semantic var

tutorialsarxiv-cs-cv

Tutorials

Logic-Guided Data Extraction with Answer Set Programming and Large Language Models

arXiv:2607.19365v1 Announce Type: new Abstract: When Large Language Models (LLMs) are used for semantic data extraction from unstructured text, producing candidate relational facts from natural langua

tutorialsarxiv-cs-ai

Matching Ranks Over Probability Yields Truly Deep Safety Alignment

arXiv:2512.05518v2 Announce Type: replace-cross Abstract: Open-source Large Language Models (LLMs) play a critical role in the democratization of AI, yet their 'open' nature introduces more avenues fo

Model 'distillation' accusations are getting way overblown at this point

model-releasesr-localllama

The news about Anthropic settling a class action lawsuit for 1.5B over training data isn't just a legal headache for them, it's a massive warning sign for engineering teams relying entirely on closed

Model Gateway: Management Platform for Model-Driven Drug Discovery

arXiv:2512.05462v2 Announce Type: replace-cross Abstract: Pharmaceutical drug discovery demands machine learning (ML) infrastructure that goes beyond general-purpose Machine Learning Operations (MLOps

Local Ai

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement

arXiv:2607.17967v2 Announce Type: replace Abstract: Monocular geometry estimation has recently achieved impressive performance across diverse scenes. However, state-of-the-art models still face notabl

local-aiarxiv-cs-cv

Multi-Resolution Voxelized Map-Based Stereo Visual-Inertial Odometry

arXiv:2607.17332v2 Announce Type: replace Abstract: Incorporating prior maps significantly enhances the accuracy and robustness of pose estimation in visual-inertial odometry (VIO). However, the large

researcharxiv-cs-ro

Multi-stage Dynamic Selection for Cross-Project Defect Prediction

arXiv:2607.20151v1 Announce Type: cross Abstract: Cross-Project Defect Prediction (CPDP) involves building models using data from external projects, called training projects, to predict modules from t

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?

arXiv:2607.20284v1 Announce Type: new Abstract: The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU

No Training, Better Flights: Test-Time Scaled VLMs for UAV Navigation

arXiv:2607.19288v1 Announce Type: new Abstract: Test-time scaling offers a promising method to improve the inference performance of Vision-Language Models (VLMs) without additional training. Existing

safetyarxiv-cs-cv

Nonlinear Bias-Compensated Adaptive Filter and Its Application for Time-Series Prediction

arXiv:2607.19902v1 Announce Type: new Abstract: Most existing nonlinear adaptive filtering algorithms only account for output noise, neglecting the fact that input noise is also prevalent in practice.

Not All Patches are Equal: Sampling Matters for Visible-Infrared Pre-Training

model-releasesarxiv-cs-cv

arXiv:2607.20238v1 Announce Type: new Abstract: Visible-infrared (VIS-IR) alignment is a key pre-training task for robust multi-sensor perception. Most existing methods use uniform patch-wise contrast

Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention

arXiv:2607.18112v2 Announce Type: replace Abstract: Panoptic segmentation in complex scenes remains challenging because of occlusions, yet modern approaches often neglect occlusion modelling. In this

On the Computational Complexity of Structural Generalization

model-releasesarxiv-cs-cl

arXiv:2607.19573v1 Announce Type: new Abstract: Structural generalization has been measured repeatedly by several benchmarks, yet it has never been formally defined. We give a definition that translat

On the Separability of Information in Diffusion Models

arXiv:2509.23937v5 Announce Type: replace-cross Abstract: Diffusion models transform noise into data by injecting information that was captured in their neural network during the training phase. In th

researcharxiv-cs-ai

Agents

one thing i think people dont appreciate enough about @poolsideai is their unusual degree of openness — not only have they shipped an excell…

one thing i think people dont appreciate enough about @poolsideai is their unusual degree of openness — not only have they shipped an excellent Small model that somehow beat @thinkymachines at coding,

agentsswyx--x

Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering

arXiv:2607.19867v1 Announce Type: cross Abstract: FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence. Each final-test item pairs an English question w

researcharxiv-cs-ai

Pathologist Attention-Aligned Report Generation for Prostate Histopathology

arXiv:2607.19624v1 Announce Type: new Abstract: The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracte

safetyarxiv-cs-cv

Physics-Aware Complex-Valued State Space Model with Scattering-Prior Feature Modulation for PolSAR Image Classification

arXiv:2607.19787v1 Announce Type: cross Abstract: Polarimetric synthetic aperture radar (PolSAR) image classification is a representative task for physics-aware GeoAI, where land-cover semantics are c

Pixel-Space Diffusion Transformers

arXiv:2607.17585v2 Announce Type: replace Abstract: Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual

Position: The Inevitable Transition to Machine Learning in Quantum Chemistry

arXiv:2607.18281v2 Announce Type: replace-cross Abstract: Finding exact solutions to the quantum many-body problem is computationally intractable (QMA-hard). Traditional approximations for electrons i

Predictive Extrema, Unprofitable Policies: An AI-Assisted Audit of Candle-Based Binance Spot Timing Models

arXiv:2607.19453v1 Announce Type: cross Abstract: We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance S

Prompt Programming for Cultural Bias and Alignment of Large Language Models

arXiv:2603.16827v2 Announce Type: replace Abstract: Culture shapes reasoning, values, prioritization, and strategic decision-making, yet large language models (LLMs) often exhibit cultural biases that

Rater State Bias in RLHF Preference Data: An Audit Framework

arXiv:2607.16195v2 Announce Type: replace Abstract: We identify a structured confound in Reinforcement Learning from Human Feedback (RLHF). Pairwise preference labels are intended to reflect the compa

Reliability-Aware Hard--Soft Physics-Informed Neural Networks for Robust Learning of Challenging Partial Differential Equations

arXiv:2607.19377v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a mesh-free framework for solving partial differential equations, but their training is often affecte

Robots Acquire Manipulation Skills in Seconds from a Single Human Video

arXiv:2607.20033v1 Announce Type: new Abstract: The ability to acquire skills rapidly and effortlessly while retaining those already mastered is essential for robots. However, current methods still re

researcharxiv-cs-ro

Local Ai

Robust Activation Map Rectification for Weakly Supervised Volumetric Segmentation: Temporal Coherence as a Free Lunch

arXiv:2607.19877v1 Announce Type: new Abstract: Weakly supervised segmentation relies heavily on class activation maps (CAMs) to initially localize target regions. However, CAMs are often noisy and pr

local-aiarxiv-cs-cv

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling

arXiv:2607.19776v1 Announce Type: cross Abstract: Existing symbolic music generation models typically use bars as the basic structural unit. However, human perception of musical phrases often does not

researcharxiv-cs-ai

Safe Remediation as Risk-Constrained Intervention Decision in Microservice Systems

arXiv:2607.20005v1 Announce Type: new Abstract: In modern IT operations (IT-Ops), the cost of an incorrect repair often exceeds the cost of no action at all. Yet existing automated remediation systems

Agents

Sarus: Privacy-Preserving Multi-Vendor Perception Fusion via Homomorphic Encryption

arXiv:2607.19146v1 Announce Type: cross Abstract: Cooperative perception enables autonomous vehicles (AVs) to improve situational awareness by aggregating detection outputs from multiple agents and se

agentsarxiv-cs-cv

Hardware

Scaling Time Series Classification via XAI-Driven Data Reduction

arXiv:2607.15774v2 Announce Type: replace-cross Abstract: Explainable AI (XAI) for time series has seen significant algorithmic growth, but its utility in providing measurable performance gains for do

hardwarearxiv-cs-ai

Seeing Before Generating: Object Perception Enhances Single-View 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2607.18630v1 Announce Type: new Abstract: The relationship between object perception and reconstruction is well established in human vision, yet remains underexplored in computer vision. In this

Simulating Eutopia: Revisiting Long-term Fairness with Outcomes, Performativity, and Dynamics

arXiv:2607.19389v1 Announce Type: cross Abstract: As AI-driven Decision Makers (ADMs) influence our socioeconomic reality, their roles in both enhancing efficiency and amplifying the social biases hav

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis

arXiv:2607.20216v1 Announce Type: cross Abstract: Malware analysis demands rapid interpretation of complex detonation reports spanning filesystem, network, and process behaviours. While large language

Spectral DPPs via NEPv: A Scalable Continuous Relaxation of Determinantal MAP for Diversity-Aware Data Selection

arXiv:2606.19411v2 Announce Type: replace Abstract: Selecting a small, diverse, high-quality subset from a massive pool of candidates is a recurring primitive in modern machine learning -- data curati

Statistical Inference for Rank Allocation in Low-Rank Adaptation

arXiv:2607.20205v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has become a widely used parameter-efficient fine-tuning method for large language models. Since different modules and laye

SUM: Unified Geometric Surgery on Spatio-Temporal Adaptation Vectors for Federated Class Incremental Learning

arXiv:2607.19384v1 Announce Type: new Abstract: Real-world intelligent systems often require both distributed collaboration across data-isolated clients and continual adaptation to evolving tasks. Thi

The C-index illusion: discrimination without calibration in published survival models

arXiv:2607.19526v1 Announce Type: new Abstract: 'Stop Chasing the C-index when Evaluating Survival Analysis Models' (ICML 2026, Spotlight) argued normatively, on synthetic data, that evaluating surviv

The Mechanism Matters: When Knowledge Graphs Help Reinforcement Learning

arXiv:2607.19616v1 Announce Type: new Abstract: Knowledge graphs (KGs) are widely used to inject prior knowledge into reinforcement learning (RL), yet the literature is dominated by single-domain, pos

Toward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Types

arXiv:2607.19994v2 Announce Type: new Abstract: Sentinel-2 imagery offers open access, global coverage, and frequent revisit times, making it attractive for practical building mapping at scale; howeve

Towards Miniature Humanoid Tele-Loco-Manipulation Using Virtual Reality and Reinforcement Learning

arXiv:2607.20399v1 Announce Type: cross Abstract: Full-sized humanoid robot capabilities have grown exponentially in recent years, aiming towards general-purpose deployment in human environments. A po

Towards Torque-Driven Reinforcement Learning for Quadruped Locomotion

arXiv:2607.18365v1 Announce Type: cross Abstract: Reinforcement learning (RL) for legged robots is advancing locomotion, demonstrating its ability to adapt to new and challenging terrain. Traditionall

TRUST-ESD: A Risk-Calibrated and Governance-Aware AI Framework for Enterprise Strategic Decision Support Under Uncertainty

arXiv:2607.20065v1 Announce Type: new Abstract: Enterprise strategic decision support requires AI systems that are not only accurate, but also uncertainty-aware, risk-calibrated, explainable, and gove

Trusted Multi-View Deep Learning Classification of Fetal Congenital Heart Disease with Feature-level and Decision-level Fusion

model-releasesarxiv-cs-cv

arXiv:2606.15265v2 Announce Type: replace Abstract: Congenital heart disease (CHD) refers to the abnormal anatomical structure caused by the abnormal development of the heart and great vessels during