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A Unified Perspective for Learning Graph Representations Across Multi-Level Abstractions

model-releasesarxiv-cs-ai

arXiv:2605.12685v1 Announce Type: cross Abstract: Graph Self-Supervised Learning (GSSL) has emerged as a powerful paradigm for generating high-quality representations for graph-structured data. While

Content type

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Applications

A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing

DGX agent

arXiv:2605.13464v1 Announce Type: new Abstract: Diabetes mellitus affects over 537 million adults worldwide and remains a major challenge in preventive healthcare. Existing machine-learning studies pr

applicationsarxiv-cs-lg

14 May 2026

A3 : an Analytical Low-Rank Approximation Framework for Attention

model-releasesarxiv-cs-ai

arXiv:2505.12942v4 Announce Type: replace-cross Abstract: Large language models have demonstrated remarkable performance; however, their massive parameter counts make deployment highly expensive. Low-

A_3B_2: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning

arXiv:2605.13161v1 Announce Type: new Abstract: Efficient transfer learning methods for large-scale vision-language models (e.g., CLIP) enable strong few-shot transfer, yet existing adaptation methods

safetyarxiv-cs-cv

Applications

Abridge: 100M+ medical conversations, real-time prior auth, and the clinical intelligence layer https://www.latent.space/p/abridge @AbridgeH…

applicationsharrison-chase--x

Abridge: 100M+ medical conversations, real-time prior auth, and the clinical intelligence layer https://www.latent.space/p/abridge @AbridgeHQ is building the clinical intelligence layer for healthcare

Accelerating Particle-based Energetic Variational Inference

arXiv:2504.03158v2 Announce Type: replace-cross Abstract: In this work, we propose a new particle-based variational inference (ParVI) method for accelerating the Energetic Variational Inference with I

researcharxiv-cs-lg

Achieving epsilon^{-2} Sample Complexity for Single-Loop Actor-Critic under Minimal Assumptions

arXiv:2605.13639v1 Announce Type: new Abstract: In this paper, we establish last-iterate convergence rates for off-policy actor--critic methods in reinforcement learning. In particular, under a single

Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling

arXiv:2605.13301v1 Announce Type: new Abstract: Recent progress in reasoning models has substantially advanced long-horizon mathematical and scientific problem solving, with several systems now reachi

AcquisitionSynthesis: Targeted Data Generation using Acquisition Functions

arXiv:2605.13149v1 Announce Type: cross Abstract: Data quality remains a critical bottleneck in developing capable, competitive models. Researchers have explored many ways to generate top quality samp

Action Emergence from Streaming Intent

model-releasesarxiv-cs-cv

arXiv:2605.12622v1 Announce Type: cross Abstract: We formalize action emergence as a target capability for end-to-end autonomous driving: the ability to generate physically feasible, semantically appr

Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations

arXiv:2605.12569v1 Announce Type: cross Abstract: Global navigation satellite system (GNSS) interference poses a serious threat to reliable positioning, especially in indoor and multipath-rich environ

AdaFocus: Adaptive Relevance-Diversity Sampling with Zero-Cache Look-back for Efficient Long Video Understanding

arXiv:2605.12954v1 Announce Type: cross Abstract: Long video understanding is heavily bottlenecked by a rigid one-shot paradigm: existing methods either densely encode videos at prohibitive memory and

Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization

arXiv:2605.12878v1 Announce Type: cross Abstract: We propose Adam-SHANG, a Lyapunov-guided Adam-type method that couples momentum, adaptive preconditioning, and a curvature-aware correction through a

Adaptive Conformal Prediction for Reliable and Explainable Medical Image Classification

arXiv:2605.12917v1 Announce Type: new Abstract: Deep learning models for medical imaging often exhibit overconfidence, creating safety risks in ambiguous diagnostic scenarios. While Conformal Predicti

safetyarxiv-cs-cv

Adaptive Kernel Density Estimation with Pre-training

arXiv:2605.13092v1 Announce Type: cross Abstract: Density estimation in high-dimensional settings is an important and challenging statistical problem.Traditional methods based on kernel smoothing are

local-aiarxiv-cs-lg

Adaptive mine planning under geological uncertainty: A POMDP framework for sequential decision-making

arXiv:2605.13702v1 Announce Type: new Abstract: Strategic mine production scheduling under geological uncertainty is conventionally formulated as a stochastic optimization problem in which a fixed ext

Adaptive Smooth Tchebycheff Attention for Multi-Objective Policy Optimization

arXiv:2605.12771v1 Announce Type: cross Abstract: Multi-objective reinforcement learning in robotic domains requires balancing complex, non-convex trade-offs between conflicting objectives. While line

AdaptNC: Adaptive Nonconformity Scores for Conformal Prediction under Distribution Shift

arXiv:2602.01629v2 Announce Type: replace Abstract: Rigorous uncertainty quantification is essential for the safe deployment of autonomous systems in unconstrained environments. Conformal Prediction (

Addressing Finite-Horizon MDPs via Low-Rank Tensor Value Approximation

arXiv:2501.10598v3 Announce Type: replace Abstract: We study the problem of learning optimal policies in finite-horizon Markov Decision Processes (MDPs) using low-rank reinforcement learning (RL) meth

Tools

after 15 years of waiting, the developers of singapore gave up on waiting for the government to get the tech sector going and finally brough…

after 15 years of waiting, the developers of singapore gave up on waiting for the government to get the tech sector going and finally brought SF to SG. great showings from @daytonaio @usetusk @arizeai

toolsswyx--x

Agent observability is a means to an end: making your agent better. But observability and evals tools have traditionally failed to connect t…

Agent observability is a means to an end: making your agent better. But observability and evals tools have traditionally failed to connect traces to meaningful actions. Agent engineering teams are lef

agentsharrison-chase--x

Agentic Interpretation: Lattice-Structured Evidence for LLM-Based Program Analysis

arXiv:2605.12694v1 Announce Type: cross Abstract: Large language models can consult information that fixed static analyzers cannot, such as documentation, current security advisories, version-specific

AgenticAITA: A Proof-Of-Concept About Deliberative Multi-Agent Reasoning for Autonomous Trading Systems

arXiv:2605.12532v1 Announce Type: cross Abstract: Conventional algorithmic trading systems are grounded in deterministic heuristics or offline-trained statistical models that cannot adapt to the seman

AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub

arXiv:2604.03551v2 Announce Type: replace-cross Abstract: Software Engineering 3.0 marks a paradigm shift in software development, in which AI coding agents are no longer just assistive tools but acti

AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation

arXiv:2605.12925v1 Announce Type: cross Abstract: Evaluation of software engineering (SWE) agents is dominated by a binary signal: whether the final patch passes the tests. This outcome-only view trea

Agents feedback tip

This article likely provides practical advice on how to effectively give feedback to AI agents or autonomous systems, covering techniques for improving agent performance through constructive feedback

industryben-s-bites

AGOP as Explanation: From Feature Learning to Per-Sample Attribution in Image Classifiers

model-releasesarxiv-cs-lg

arXiv:2605.12816v1 Announce Type: new Abstract: The Average Gradient Outer Product (AGOP) governs feature learning in neural networks: the Neural Feature Ansatz states that weight Gram matrices at eac

AI co-mathematician: Accelerating mathematicians with agentic AI

arXiv:2605.06651v2 Announce Type: replace Abstract: We introduce the AI co-mathematician, a workbench for mathematicians to interactively leverage AI agents to pursue open-ended research. The AI co-ma

AI-Generated Slides: Are They Good? Can Students Tell?

model-releasesarxiv-cs-ai

arXiv:2605.13532v1 Announce Type: new Abstract: As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines u

AI Harness Engineering: A Runtime Substrate for Foundation-Model Software Agents

arXiv:2605.13357v1 Announce Type: cross Abstract: Foundation models have transformed automated code generation, yet autonomous software-engineering agents remain unreliable in realistic development se

Applications

AI-Native Healthcare: 100M Doctor Visits, 10–20 Hours Saved, Prior Auth in Minutes — Janie Lee & Chai Asawa, Abridge

Abridge has developed AI-native healthcare solutions that have facilitated 100 million doctor visits while saving patients and providers 10-20 hours collectively, with particular efficiency gains in p

applicationslatent-space

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions

arXiv:2408.12935v4 Announce Type: replace Abstract: AI Safety is an emerging area of critical importance to the safe adoption and deployment of AI systems. With the rapid proliferation of AI and espec

AI training data provider Wirestock raises $23M in funding

Wirestock Inc., a startup that provides multimodal training datasets for artificial intelligence developers, has raised 23 million in funding. TechCrunch reported today that early-stage fund Nava Vent

industrysiliconangle

[AINews] Codex Rises, Claude Meters Programmatic Usage

model-releaseslatent-space

This AINews roundup from Latent Space likely covers updates on OpenAI's Codex model gaining prominence in code generation applications, alongside news about Anthropic's Claude implementing usage meter

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

arXiv:2502.15761v3 Announce Type: replace-cross Abstract: The deployment of large language models (LLMs) on extended reality (XR) devices has great potential to advance the field of human-AI interacti

Aleph, our fully autonomous AI agent system for formal verification, aced all major theorem proving benchmarks including PutnamBench, VeriSo…

Aleph is a fully autonomous AI agent system developed for formal verification that has achieved top performance across major theorem proving benchmarks, including PutnamBench and VeriSo. The system re

agentsyann-lecun--x

Aligning Forest and Trees in Images & Long Captions for Visually Grounded Understanding

arXiv:2602.02977v2 Announce Type: replace-cross Abstract: Vision-language models such as CLIP often struggle to faithfully understand long, detail-rich captions, relying on dominant scene cues while o

Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration

arXiv:2605.13744v1 Announce Type: new Abstract: Image restoration is an inherently ill posed inverse problem. Equivariant networks that embed geometric symmetry priors can mitigate this ill posedness

safetyarxiv-cs-cv

Applications

all of their ideas now are like “should we dissolve the government, imprison our opponents, and seize every lever of power in the country? w…

all of their ideas now are like “should we dissolve the government, imprison our opponents, and seize every lever of power in the country? we’re the good guys remember, if we don’t do this the bad guy

applicationselon-musk--x

Hardware

almost all LLM “thought” is derivative. below just sounds like hype to me

almost all LLM “thought” is derivative. below just sounds like hype to me 📁 Jensen Huang, CEO of NVIDIA, says GPT was never just about generating images or text but about generating thought itself. Th

hardwaregary-marcus--x

Alphabet sold $3.6B of bonds in its debut yen-denominated bond sale, the largest by a non-Japanese company, as AI-driven capital spending accelerates (Atsuko Fukase/Bloomberg)

Atsuko Fukase / Bloomberg: Alphabet sold 3.6B of bonds in its debut yen-denominated bond sale, the largest by a non-Japanese company, as AI-driven capital spending accelerates — Alphabet Inc. sold ¥57

industrytechmeme

also all this:

also all this: Codex is getting easier to automate and customize around your code. 🪝 Hooks customize the Codex loop with scripts that run at key points in a task: • Run validators before or after work

industrysam-altman--x

Americans do not want AI data centers in their backyards

Over 70 percent of Americans oppose AI data center construction in their area, according to a new Gallup survey. Just 7 percent said they were 'strongly' in favor of new data centers. According to Gal

industrythe-verge-ai

Amortized Guidance for Image Inpainting with Pretrained Diffusion Models

arXiv:2605.13010v1 Announce Type: cross Abstract: We study image inpainting with generative diffusion models. Existing methods typically either train dedicated task-specific models, or adapt a pretrai

Amortized Neural Clustering of Time Series based on Statistical Features

arXiv:2605.13128v1 Announce Type: cross Abstract: This paper introduces an algorithm-agnostic approach to feature-based time series clustering via amortized neural inference. By training neural networ

researcharxiv-cs-lg

Amplification to Synthesis: A Comparative Analysis of Cognitive Operations Before and After Generative AI

arXiv:2605.13785v1 Announce Type: cross Abstract: Cognitive operations are a rising concern in the geopolitical sphere, a quiet yet rigorous fight for public perception and decision making. While such

An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing

arXiv:2605.13221v1 Announce Type: new Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC). This joint operation forms

An Agentic LLM-Based Framework for Population-Scale Mental Health Screening

arXiv:2605.13046v1 Announce Type: new Abstract: Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical data generated from ele