Search: “research”

Automated ICD Classification of Psychiatric Diagnoses: From Classical NLP to Large Language Models

arXiv:2605.21154v1 Announce Type: new Abstract: Mental health has become a global priority, leading to a massive administrative burden in the coding of clinical diagnoses. This study proposes the auto

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Can Vision Models Truly Forget? Mirage: Representation-Level Certification of Visual Unlearning

DGX agent

arXiv:2605.20282v1 Announce Type: new Abstract: Machine unlearning in Vertical Federated Learning (VFL) has attracted growing interest, yet existing methods certify forgetting solely using output-leve

safetyarxiv-cs-cv

21 May 2026

CoarseSoundNet: Building a reliable model for ecological soundscape analysis

arXiv:2605.21143v1 Announce Type: cross Abstract: A soundscape is composed of three types of sound: biophony (sounds made by animals), geophony (natural abiotic sounds) and anthropophony (sounds made

applicationsarxiv-cs-lg

Comparative Analysis of Military Detection Using Drone Imagery Across Multiple Visual Spectrums

arXiv:2605.21157v1 Announce Type: new Abstract: In modern warfare, drones are becoming an essential part of intelligence gathering and carrying out precise attacks in different kinds of hostile enviro

applicationsarxiv-cs-cv

DarkShake-DVS: Event-based Human Action Recognition under Low-light andShaking Camera Conditions

arXiv:2605.20680v1 Announce Type: new Abstract: Human Action Recognition (HAR) is a fundamental computer vision task with diverse real-world applications. Practical deployments often involve low-light

Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning

arXiv:2605.20730v1 Announce Type: new Abstract: In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks through demonstrations, yet it suffers from escalating inference cos

safetyarxiv-cs-cl

Do No Harm? Hallucination and Actor-Level Abuse in Web-Deployed Medical Large Language Models

arXiv:2605.20591v1 Announce Type: new Abstract: Medical large language models (LLMs), including custom medical GPTs (MedGPTs) and open-source models, are increasingly deployed on web platforms to prov

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DriveMA: Rethinking Language Interfaces in Driving VLAs with One-Step Meta-Actions

arXiv:2605.21273v1 Announce Type: new Abstract: Driving Vision-Language-Action Models (Driving VLAs) commonly introduce natural-language reasoning as an intermediate interface for end-to-end planning,

Findings of the Counter Turing Test: AI-Generated Image Detection

arXiv:2605.20787v1 Announce Type: new Abstract: The rapid advancements in generative AI technologies, such as Stable Diffusion, DALL-E, and Midjourney, have significantly transformed the creation of s

applicationsarxiv-cs-cv

Findings of the Counter Turing Test: AI-Generated Text Detection

arXiv:2605.20761v1 Announce Type: new Abstract: The rapid proliferation of AI-generated text has introduced significant challenges in maintaining the integrity of digital content. Advanced generative

FineVision: Open Data Is All You Need

arXiv:2510.17269v2 Announce Type: replace Abstract: The advancement of vision-language models (VLMs) is hampered by a fragmented landscape of inconsistent and contaminated public datasets. We introduc

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Industry

FWIW, I think this moves up my AI timelines a bit. I think the next milestone will be 'Artificial Grothendieck Intelligence' (AGrI): defin…

FWIW, I think this moves up my AI timelines a bit. I think the next milestone will be 'Artificial *Grothendieck* Intelligence' (AGrI): defining new general mathematical structures to solve the hardest

industryemad-mostaque--x

Tutorials

Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation

arXiv:2605.20600v1 Announce Type: new Abstract: Autoregressive (AR) visual generation has achieved remarkable performance but suffers from high memory usage and low throughput, as it requires caching

tutorialsarxiv-cs-cv

He's right. And it has a direct implication for code review that nobody's talking about. Think about why AI cracked coding before almost eve…

He's right. And it has a direct implication for code review that nobody's talking about. Think about why AI cracked coding before almost everything else. Not because code is simple. Because code is ch

agentsitamar-friedman--x

How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study

arXiv:2604.06750v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) are increasingly proposed for autonomous driving tasks, yet their performance on sequential driving scenes remains poo

agentsarxiv-cs-cv

Improving Quantized Model Performance in Qualitative Analysis with Multi-Pass Prompt Verification

arXiv:2605.20193v1 Announce Type: new Abstract: Quantized Large Language Models (LLMs) are used more often in qualitative analysis because they run fast and need fewer computing resources. This study

Intelligent radiology workflow optimization with AI agents

Many healthcare organizations report that traditional worklist systems rely on rigid rules that ignore critical context, radiologist specialization, current workload, fatigue levels, and case complexi

applicationsaws-ml-blog

InternBootcamp Technical Report: Boosting LLM Reasoning with Verifiable Task Scaling

arXiv:2508.08636v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized artificial intelligence by enabling complex reasoning capabilities. While recent advancements in re

JobArabi: An Arabic Corpus and Analysis of Job Announcements from Social Media

arXiv:2605.20960v1 Announce Type: new Abstract: This paper introduces JobArabi, a large-scale corpus of Arabic job announcements collected from social media between January 2024 and October 2025. The

Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search

arXiv:2605.20244v1 Announce Type: cross Abstract: We present Lean Refactor, a plug-and-play retrieval-augmented agentic framework for multi-objective, controllable, and version-robust refactoring of L

Leveraging Vision-Language Models to Detect Attention in Educational Videos

arXiv:2605.20211v1 Announce Type: new Abstract: Educational videos are a cornerstone of remote and blended learning. However, learners' fluctuating attention remains a significant barrier to effective

Measuring and mitigating overreliance to build human-compatible AI

arXiv:2509.08010v2 Announce Type: replace-cross Abstract: Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable o

applicationsarxiv-cs-cl

MemGym: a Long-Horizon Memory Environment for LLM Agents

arXiv:2605.20833v1 Announce Type: new Abstract: Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of person

MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks

arXiv:2605.20729v1 Announce Type: new Abstract: Accurate evaluation of conversational retrieval is pivotal for advancing Retrieval-Augmented Generation (RAG) systems. However, existing conversational

Multi-Week, In-Class Deployments of Telepresence Robots With Four Homebound K-12 Students: Benefits, Challenges, and Recommendations

arXiv:2605.20431v1 Announce Type: cross Abstract: Missing significant amounts of school during K-12 education is known to put students' cognitive and social development at risk. Alternatives such as h

applicationsarxiv-cs-ro

Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches

arXiv:2510.04905v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved

agentsarxiv-cs-cl

ShadeBench: A Benchmark Dataset for Building Shade Simulation in Sustainable Society

arXiv:2605.20510v1 Announce Type: new Abstract: Urban heat exposure is becoming an increasingly critical challenge due to the intensifying urban heat island effect. Fine-grained shade patterns, especi

Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs

arXiv:2605.20191v1 Announce Type: new Abstract: Modern Large Language Models (LLMs) have recently attracted much attention for their ability to simulate human behavior and generate text that reflects

safetyarxiv-cs-cl

Smaller Abstract State Spaces Enable Cross-Scale Generalization in Reinforcement Learning

arXiv:2605.20272v1 Announce Type: new Abstract: While humans readily generalize abstract concepts to more complex or larger tasks, building Reinforcement Learning (RL) systems with this ability remain

agentsarxiv-cs-lg

SubTGraph: Large-Scale Subterranean Environment Synthesis with Controllable Topological Variability for Robotic Autonomy Validation

arXiv:2605.20917v1 Announce Type: new Abstract: Subterranean (SubT) environments have been a frontier for autonomous robotics, driven by the push for automation of mining operations and the interest i

agentsarxiv-cs-ro

Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecasting

arXiv:2506.17631v4 Announce Type: replace Abstract: Time series forecasting aims to model temporal dependencies among variables for future state inference, holding significant importance and widesprea

safetyarxiv-cs-lg

Towards UAV Detection in the Real World: A New Multispectral Dataset UAVNet-MS and a New Method

arXiv:2605.20963v1 Announce Type: new Abstract: The proliferation of unmanned aerial vehicles (UAVs) has created urgent demand for precise UAV monitoring. Existing RGB-based systems rely on spatial cu

Training Language Agents to Learn from Experience

arXiv:2605.20477v1 Announce Type: cross Abstract: Language agents can adapt from experience in interactive environments, but current reflection-based methods can only self-correct within a single task

Understanding and Improving Communication Performance in Multi-node LLM Inference

model-releasesarxiv-cs-lg

arXiv:2511.09557v4 Announce Type: replace-cross Abstract: As large language models (LLMs) continue to grow in size, distributed inference has become increasingly important. Model-parallel strategies m

Industry

US government takes $2 billion equity stake in nine quantum computing firms

The Trump administration awarded $2 billion in grants to nine quantum-computing companies through deals that include U.S. government equity stakes , marking a departure from traditional government fun

industryars-technica

We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risks

model-releasesgoogle-deepmind

Google DeepMind has launched 'AI for the Planet,' a three-month accelerator program in Asia Pacific focused on leveraging advanced AI to combat environmental challenges like climate change, biodiversi

A Reproducibility Analysis of PO4ISR: Diagnosing and Mitigating Semantic Drift in LLM-Based Session Recommendation

arXiv:2605.18780v1 Announce Type: cross Abstract: Reasoning-based Large Language Models (LLMs) like PO4ISR have set new benchmarks in session-based recommendation. However, the reproducibility of thei

Hardware

Accelerating Sparse Transformer Inference on GPU

arXiv:2506.06095v4 Announce Type: replace Abstract: Large language models (LLMs) are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerat

hardwarearxiv-cs-lg

An OpenAI model has disproved a central conjecture in discrete geometry

An OpenAI AI model successfully disproved a longstanding conjecture in discrete geometry, a mathematical field studying geometric properties of discrete objects. This achievement demonstrates the pote

model-releasesopenai

Tutorials

BCI-sift: An automated feature selection toolbox for Brain Computer Interface applications

arXiv:2605.19646v1 Announce Type: cross Abstract: Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and nois

tutorialsarxiv-cs-lg

BLINKG: A Benchmark for LLM-Integrated Knowledge Graph Generation

arXiv:2605.19518v1 Announce Type: new Abstract: Generating Knowledge Graphs (KGs) remains one of the most time-consuming and labor-intensive tasks for knowledge engineers, as they need to identify sem

⚠️👇 🚨Breaking ⚠️ If we can’t make AI agents follow rules, we are screwed. New study from METR reports that “when the agents were faced wit…

⚠️👇 🚨Breaking ⚠️ If we can’t make AI agents follow rules, we are screwed. New study from METR reports that “when the agents were faced with hard tasks, they routinely violated constraints” This—routin

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CAIT: A Syntactic Parsing Toolkit for Child-Adult InTeractions

arXiv:2605.19718v1 Announce Type: new Abstract: CHILDES is a paramount resource for language acquisition studies -- yet computational tools for analyzing its syntactic structure remain limited. Levera

applicationsarxiv-cs-cl

CogScale: Scalable Benchmark for Sequence Processing

arXiv:2605.19758v1 Announce Type: new Abstract: The ability to maintain and manipulate information over time is a fundamental aspect of living beings and Artificial Intelligence. While modern models h

Decentralized autonomous organization and blockchain-based incentivization framework for community-based facilities management

arXiv:2605.18773v1 Announce Type: cross Abstract: Traditional facility management often relies on centralized decision-making structures that limit stakeholder participation, leading to misalignment w

agentsarxiv-cs-ai

Discoverable Agent Knowledge -- A Formal Framework for Agentic KG Affordances (Extended Version)

arXiv:2605.19186v1 Announce Type: new Abstract: Two decades ago, the Semantic Web Services community was asked how agents with different ontological commitments could discover, compose, and invoke web

agentsarxiv-cs-ai

Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL

arXiv:2603.23722v2 Announce Type: replace-cross Abstract: While Multi-Agent Reinforcement Learning (MARL) algorithms achieve unprecedented successes across complex continuous domains, their standard d

safetyarxiv-cs-lg

EgoBabyVLM: Benchmarking Cross-Modal Learning from Naturalistic Egocentric Video Data

arXiv:2605.19130v1 Announce Type: cross Abstract: Children acquire language grounding with remarkable robustness from limited visuo-linguistic input in ways that surpass today's best large multimodal