Search: “models”

Retrieval, not hallucinations, will be the limiting factor for LLM-based clinical AI tools

arXiv:2607.24793v1 Announce Type: cross Abstract: Discussions around large language model (LLM) errors in clinical artificial intelligence (AI) generally center around precision errors like hallucinat

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Research

Right-sizing Recommendations (RSR): Cloud Workload Conformal Prediction for Virtual Machines in Data Center Operations

DGX agent

arXiv:2607.24773v1 Announce Type: new Abstract: Managing cloud infrastructure efficiently, especially in environments of large cloud providers or hyperscalers, requires optimizing the use of physical

researcharxiv-cs-ai

29 Jul 2026

RoCo-ACE: Rollout-Conditioned Online Distillation for Retention-Aware Knowledge Injection

arXiv:2607.24771v1 Announce Type: new Abstract: Knowledge injection updates pretrained MLLMs with new factual or domain-specific knowledge, but fitting full authoritative answers can cause drift in no

Safety-Aware Cascaded Inference for Crop Damage Assessment with Controlled Error Trade-offs

arXiv:2607.25468v1 Announce Type: new Abstract: In picture-based agricultural insurance for smallholder farmers, missed damage detections carry substantially higher cost than false alarms: a farmer wh

safetyarxiv-cs-cv

Sakana is at the frontier of having fun and I respect that

Sakana is at the frontier of having fun and I respect that We are excited to share our latest work, together with @nyuniversity: 'Dream-Cubed: Controllable Generative Modeling in Minecraft by Training

agentsjerry-liu--x

Score-Based Stabilization for Time-Dependent Problems

arXiv:2607.25119v1 Announce Type: new Abstract: We propose a score-based stabilization framework for numerical simulation of partial differential equations, in which a learned score model defines a st

SearchArt: Training Long-Horizon Search Agent with Scalable Synthetic and Verified Task

arXiv:2607.24850v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled search agents to autonomously tackle complex tasks across extended search and reasoning h

safetyarxiv-cs-lg

Selective Impairment of Motor Recovery from Typing Errors in Parkinson's Disease: A Survival Analysis

arXiv:2607.24796v1 Announce Type: cross Abstract: Parkinson's disease (PD) affects multiple, dissociable stages of motor and cognitive control. We ask whether passively-collected keystroke dynamics ca

Shared Voxel-Map-Based Cooperative Indoor UAV Guidance with a Multi-Agent Soft Actor-Critic Controller

arXiv:2607.25728v1 Announce Type: cross Abstract: This paper presents a cooperative indoor UAV guidance framework that combines a shared voxel-map world model with a multi-agent Soft Actor-Critic (MAS

safetyarxiv-cs-ai

Sheet As Token: A Graph-Enhanced Representation for Multi-Sheet Spreadsheet Understanding

arXiv:2605.05811v2 Announce Type: replace Abstract: Workbook-scale spreadsheet understanding is increasingly important for language-model-based data analysis agents, but remains challenging because re

Stemma: Induced Decision Regions Reveal LLM Provenance

arXiv:2607.25880v1 Announce Type: cross Abstract: LLM provenance testing asks whether a suspect LLM belongs to the same lineage as a source. Existing black-box methods largely infer this relationship

Hardware

Super interesting new work from NVIDIA. (bookmark it) They suggest building agents as Python objects. Very cool idea and I think it could a …

Super interesting new work from NVIDIA. (bookmark it) They suggest building agents as Python objects. Very cool idea and I think it could a lot with agent reliability. More below: Agent development to

hardwaredair-ai--x

Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction

arXiv:2607.25718v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on invoking external tools to complete real-world tasks. Tool retrieval, which selects a small tas

agentsarxiv-cs-ai

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories

arXiv:2412.18756v2 Announce Type: replace Abstract: A primary advantage of neural networks lies in their feature learning characteristics, which is challenging to theoretically analyze due to the comp

Hardware

Towards Embodied Cognition in Robots via Spatially Grounded Synthetic Worlds

arXiv:2505.14366v2 Announce Type: replace Abstract: We present a conceptual framework for training Vision-Language Models (VLMs) to perform Visual Perspective Taking (VPT), a core capability for embod

hardwarearxiv-cs-ai

Unifying Active Learning and Semi-Supervised Learning for Medical Image Segmentation

arXiv:2607.25014v1 Announce Type: new Abstract: In practical settings, medical image segmentation models are often developed with limited annotated data rather than fully labeled datasets. Training fr

tutorialsarxiv-cs-cv

Using Data-Derived Priors to Guide CNN Architecture Design for NIR Chemometrics

arXiv:2607.25636v1 Announce Type: new Abstract: Convolutional neural networks (CNN) for near-infrared (NIR) chemometrics are often designed using generic architectural rules, although spectral dataset

tutorialsarxiv-cs-lg

VisRAG2.0: Mitigating Visual Hallucinations via Evidence-Guided Multi-Image Reasoning in Visual Retrieval-Augmented Generation

arXiv:2510.09733v2 Announce Type: replace Abstract: Visual Retrieval-Augmented Generation (VRAG) has emerged as a promising paradigm for equipping Vision-Language Models (VLMs) with external visual ev

We’re running out of reasons to ignore AI safety

Earlier this month, OpenAI gave several of its AI models a task: complete a test designed to measure their cybersecurity capabilities. It put the systems in a sandboxed environment without an internet

safetythe-verge-ai

When Algorithms Meet Artists: Semantic Compression and Stake-holder Marginalisation in Public AI-Art Discourse (2013-2025)

arXiv:2508.03037v5 Announce Type: replace Abstract: Artists occupy a paradoxical position in generative AI. Their own work trains models that now compete with them, replicate their styles, and reshape

applicationsarxiv-cs-cl

A Formal Kinetic Theory for Zeroth-Order Newton Dynamics:Stein-Corrected Hessian Estimation and Curvature--Variance Trade-offs

arXiv:2607.22567v1 Announce Type: cross Abstract: Zeroth-order Newton-type methods are useful when gradients and Hessians are unavailable, but they behave quite differently from first-order gradient-f

ACRL: Adaptive Control of Training-Inference Discrepancy for Stable Reinforcement Learning

arXiv:2607.24062v1 Announce Type: cross Abstract: Reinforcement Learning (RL) training for Large Language Models (LLMs) often suffers from instability due to the discrepancy between training and infer

safetyarxiv-cs-ai

Agentic Autoresearch for CT Reconstruction

arXiv:2607.22824v1 Announce Type: cross Abstract: Comparing CT reconstruction methods fairly is labor-intensive and largely manual, and many benchmarks use idealized data. We ask whether a large langu

agentsarxiv-cs-ai

Local Ai

An Integrated Deep Learning and Statistical Framework for Whole-Network Gene--Environment Association with Leaf Vascular Architecture

arXiv:2607.22763v1 Announce Type: new Abstract: Leaf veins exhibit remarkable diversity in architecture and patterning, yet existing gene--environment association studies have primarily quantified lea

local-aiarxiv-cs-lg

An Interactive Vision Language Platform for Cognitive Remediation in Schizophrenia

arXiv:2607.22721v1 Announce Type: cross Abstract: Cognitive remediation tasks often require patients to perform structured actions involving object manipulation and sequential reasoning. For patients

Are Flat Minima an Illusion?

arXiv:2605.05209v2 Announce Type: replace-cross Abstract: Flat minima are an account of why deep networks generalise. However flatness is a matter of form (parameters), while generalisation is of func

safetyarxiv-cs-ai

At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone. We believe that, at some point in th…

At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone. We believe that, at some point in the future, AI acceleration for frontier model development may

tutorialsopenai--x

ATCNet-CIAM for Multi-Session Motor Imagery EEG Signal Classification

arXiv:2607.23522v1 Announce Type: new Abstract: Motor imagery (MI)-based electroencephalography is widely used in non-invasive brain--computer interfaces (BCIs), but robust decoding remains challengin

researcharxiv-cs-cv

AutoCluster, AutoTopicModeling, AutoTrendAnalysis: A Complete AutoML Pipeline for Predicting Emerging Trends

arXiv:2607.22641v1 Announce Type: cross Abstract: Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability.

BC-NMPC: Battery-Constrained NMPC with Propulsion Prediction and Replanning for High-Speed Flight

arXiv:2607.23867v1 Announce Type: new Abstract: Trajectory tracking performance of Uncrewed Aerial Vehicles (UAVs) degrades during high-speed and agile flight due to the depletion of the battery and s

applicationsarxiv-cs-ro

BeyondFusion: Self-Aligned Latent Diffusion for Calibration-Free Infrared Super-Resolution and Infrared-Visible Fusion

arXiv:2607.24110v1 Announce Type: new Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cros

tutorialsarxiv-cs-cv

BioSentinel at EXIST 2026: Soft-Label Optimization with XLM-RoBERTa for Sexism Intent Classification in Memes

arXiv:2607.24137v1 Announce Type: new Abstract: This paper describes the BioSentinel team's participation in EXIST 2026 Task 2.2: Source Intention in Memes, part of the CLEF 2026 evaluation campaign.

Local Ai

CADER: Confidence-Aware Dynamic Evidence Reasoning for Long-Video Understanding

arXiv:2607.24582v1 Announce Type: cross Abstract: Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference p

local-aiarxiv-cs-ai

CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering

arXiv:2607.24236v1 Announce Type: new Abstract: Long-form question answering increasingly relies on retrieved evidence to make LLM outputs verifiable, with inline citations tracing claims to source do

CausAdv: A Causal-based Framework for Detecting Adversarial Examples

arXiv:2411.00839v4 Announce Type: replace-cross Abstract: Deep learning has led to tremendous success in computer vision, largely due to Convolutional Neural Networks (CNNs). However, CNNs have been s

Codex from 0 to 10M Users: Building ChatGPT Work — Akshay Nathan, OpenAI

OpenAI’s Codex, an AI‑powered coding engine, has surged beyond the developer community to reach over 10 million users—combining Codex with its new “ChatGPT Work” platform that turns the model into a g

applicationslatent-space

Codifying the Judge: Scalable Evaluation via Program Distillation

arXiv:2607.22561v1 Announce Type: new Abstract: LLM-as-a-judge has become the standard for automated evaluation, but it suffers from high cost, significant latency, and opaque decisions -- limitations

ConFusion: Continuous Fusion Space Learning for Fine-Grained Controllable Infrared and Visible Image Fusion

arXiv:2607.23600v1 Announce Type: new Abstract: Controllable infrared-visible image fusion aims to integrate complementary thermal and structural information with flexible region-aware modulation, pro

safetyarxiv-cs-cv

Constrained Reinforcement Learning Using Successor Representations

arXiv:2607.24057v1 Announce Type: new Abstract: Real-world Reinforcement Learning depends on the ability to formulate safety constraints into a policy. A common way to model such constraints is to int

safetyarxiv-cs-lg

CrossSpine: Multi-scale Cross-sequence Attention with Anatomical Priors for Automated Pfirrmann Grading

arXiv:2607.22728v1 Announce Type: new Abstract: Automated grading of Lumbar Disc Degeneration is essential for the objective quantification of structural changes associated with low back pain. Observi

tutorialsarxiv-cs-cv

DECAF: De-Clustering for Adaptive Representational Unlearning

arXiv:2607.23934v1 Announce Type: new Abstract: Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability,

Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data

arXiv:2602.10381v2 Announce Type: replace Abstract: Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches ar

applicationsarxiv-cs-lg

DeepFaith: Evidence-Grounded LLMs for Faithful Incident Reporting in Multi-Stage APT Defense

arXiv:2607.24348v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are difficult to detect and interpret due to their multi-stage and stealthy nature. While recent autonomous defense

agentsarxiv-cs-ai

Hardware

Developing Healthcare Robotics with GPU-Native Medical Physics Simulation

Healthcare robotics struggles with data scarcity, limited generalization to rare clinical scenarios, and slow prototyping due to the need for annotated demonstrations and costly experimental setups. N

hardwarenvidia-developer

Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors

arXiv:2607.22935v1 Announce Type: new Abstract: Minimum-exposure constraints arise in recommendation, content curation, and regulated allocation when each provider, arm, or group must receive guarante

Disentangling Acoustic Cues in Alzheimer's Pathology and Perception: The Roles of Language and Gender

arXiv:2607.23977v1 Announce Type: cross Abstract: Acoustic biomarkers show promise for detecting Alzheimer's Disease (AD), yet whether the cues driving diagnostic AI align with those salient to human

safetyarxiv-cs-lg

DSCH-Loss: A Dynamic Semantic Channel Objective for Deep Semantic Hashing

arXiv:2607.24567v1 Announce Type: new Abstract: Semantic hashing methods for generating short binary hash codes that allow efficient approximate nearest neighbor search in high-dimensional data spaces

Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection

arXiv:2512.07246v2 Announce Type: replace Abstract: Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent s