Search: “applications”

Quantum-centric supercomputing simulates 12,635-atom protein

IBM researchers demonstrated a quantum-centric supercomputing approach that successfully simulated a protein containing 12,635 atoms in collaboration with Cleveland Clinic and RIKEN, combining classic

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Research

Revisiting Semantic Role Labeling: Efficient Structured Inference with Dependency-Informed Analysis

DGX agent

arXiv:2605.02505v1 Announce Type: new Abstract: Semantic Role Labeling (SRL) provides an explicit representation of predicate-argument structure, capturing linguistically grounded relations such as wh

researcharxiv-cs-cl

5 May 2026

SAMamba3D: adapting Segment Anything for generalizable 3D segmentation of multiphase pore-scale images

arXiv:2605.00916v1 Announce Type: new Abstract: Reliable segmentation of multiphase pore-scale X-ray images of rocks is necessary to quantify fluid saturation, connectivity, and interfacial geometry.

SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis

arXiv:2603.21783v2 Announce Type: replace Abstract: Text-to-image generation powered by Diffusion Transformers (DiTs) has made remarkable strides, yet remote sensing (RS) synthesis lags behind due to

Sim-to-Real Transfer and Robustness Evaluation of Reinforcement Learning Control with Integrated Perception on an ASV for Floating Waste Capture

arXiv:2605.02529v1 Announce Type: new Abstract: Autonomous surface vessels for floating-waste removal operate under varying hydrodynamics, external disturbances, and challenging water-surface percepti

agentsarxiv-cs-ro

SixthSense: Task-Agnostic Proprioception-Only Whole-Body Wrench Estimation for Humanoids

arXiv:2605.01427v1 Announce Type: new Abstract: Humanoid robots are entering our physical world at scale, yet as oversized toys--good at singing and dancing, but short on force-interaction capabilitie

researcharxiv-cs-ro

SparseContrast: Dynamic Sparse Attention for Efficient and Accurate Contrastive Learning in Medical Imaging

arXiv:2605.00887v1 Announce Type: new Abstract: We propose SparseContrast, a new framework that merges dynamic sparse attention with contrastive learning for medical imaging, with a focus on chest X-r

Stability and Generalization for Decentralized Markov SGD

arXiv:2605.01701v1 Announce Type: new Abstract: Stochastic gradient methods are central to large-scale learning, yet their generalization theory typically relies on independent sampling assumptions. I

Stable Blanket with Hidden Variables and Cycles

arXiv:2605.01856v1 Announce Type: cross Abstract: Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different

Super-resolution of airborne laser scanning point clouds for forest inventory

arXiv:2605.02201v1 Announce Type: new Abstract: Airborne Laser Scanning (ALS) can collect point clouds across large areas, enabling large-scale forest inventory. However, ALS point clouds are sparse a

local-aiarxiv-cs-cv

SwiftPie: Lightning-fast Subject-driven Image Personalization via One step Diffusion

arXiv:2605.01510v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in high-quality image synthesis, sparking interest in image-guided generation tasks such as subject-dr

safetyarxiv-cs-cv

Synthetic Users, Real Differences: an Evaluation Framework for User Simulation in Multi-Turn Conversations

arXiv:2605.02624v1 Announce Type: new Abstract: There is growing interest in exploring user simulation as an alternative to gathering and scoring real user-chatbot interactions for AI chatbot evaluati

researcharxiv-cs-cl

Task-Related Token Compression in Multimodal Large Language Models from an Explainability Perspective

arXiv:2506.01097v2 Announce Type: replace Abstract: Existing Multimodal Large Language Models (MLLMs) process a large number of visual tokens, leading to significant computational costs and inefficien

safetyarxiv-cs-cv

The Banach-Butterfly Invariant: Influence-Adaptive Walsh Geometry for Ternary Polynomial Threshold Functions

arXiv:2605.01637v1 Announce Type: new Abstract: We introduce the Banach-Butterfly Invariant (BBT), an influence-adaptive Banach geometry on the Walsh-Hadamard butterfly factorization. For a Boolean fu

The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification

model-releasesarxiv-cs-lg

arXiv:2510.01020v2 Announce Type: replace Abstract: We study sequential testing for a binary disease outcome when risk follows an unknown logistic model. At each round, the decision maker may either p

To Do or Not to Do: Ensuring the Safety of Visuomotor Policies Learned from Demonstrations

arXiv:2605.01201v1 Announce Type: new Abstract: Task success has historically been the primary measure of policy performance in imitation learning (IL) research. This characteristics strictly limits t

safetyarxiv-cs-ro

TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness

arXiv:2506.20588v2 Announce Type: replace Abstract: The increasing ubiquity of video content and the corresponding demand for efficient access to meaningful information have elevated video summarizati

TRIP-Evaluate: An Open Multimodal Benchmark for Evaluating Large Models in Transportation

arXiv:2605.00907v1 Announce Type: new Abstract: Large language models (LLMs) and multimodal large models (MLLMs) are increasingly used for transportation tasks such as regulation question answering, t

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

researcharxiv-cs-ai

Visual Chart Representations for Cryptocurrency Regime Prediction: A Systematic Deep Learning Study

arXiv:2605.00875v1 Announce Type: new Abstract: Technical traders have long relied on visual analysis of candlestick charts to identify market patterns and predict price movements. While deep learning

We've raised $27M to build @CopilotKit — the Agentic Frontend Stack connecting humans & agents. Because all UI will be AI. Co-led by Glilot …

CopilotKit has secured $27 million in funding to develop an agentic frontend stack that integrates AI agents with human-facing user interfaces, reflecting the belief that all future UI will incorporat

agentsharrison-chase--x

what model are you choosing for coding tasks?

This post likely discusses Harrison Chase's preferred language model or AI system for handling coding tasks, potentially comparing different models' capabilities for programming work. As the creator o

agentsharrison-chase--x

WILD SAM: A Simulated-and-Real Data Augmentation for Autonomous Driving Perception under Challenging Weather

arXiv:2605.01081v1 Announce Type: new Abstract: The performance of state-of-the-art object detectors degrades significantly under adverse weather, causing a safety-critical domain shift problem for au

Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics

arXiv:2505.13150v2 Announce Type: replace Abstract: Behavioral Foundation Models (BFMs) proved successful in producing policies for arbitrary tasks in a zero-shot manner, requiring no test-time traini

safetyarxiv-cs-lg

Zero-Shot Interpretable Image Steganalysis for Invertible Image Hiding

arXiv:2605.01331v1 Announce Type: new Abstract: Image steganalysis, which aims at detecting secret information concealed within images, has become a critical countermeasure for assessing the security

A decade of quantum on the cloud

IBM Research reflects on ten years of quantum computing development and deployment through cloud-based platforms, documenting the evolution from early experimental systems to more practical quantum pr

researchibm-research

A Unified Deep Learning Framework for Motion Correction in Medical Imaging

arXiv:2409.14204v4 Announce Type: replace-cross Abstract: Deep learning has shown significant value in medical image registration for motion correction, however, current techniques are either limited

local-aiarxiv-cs-cv

Adaptive Norm-Based Regularization for Neural Networks

arXiv:2605.00171v1 Announce Type: cross Abstract: In this paper, we study norm-based regularization methods for neural networks. We compare existing penalization approaches and introduce two regulariz

AIDA-ReID: Adaptive Intermediate Domain Adaptation for Generalizable and Source-Free Person Re-Identification

arXiv:2605.00111v1 Announce Type: new Abstract: Person re-identification (Re-ID) aims to match images of the same individual across non-overlapping camera views and remains challenging due to domain s

Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration

arXiv:2605.00310v1 Announce Type: new Abstract: Super-resolution (SR) techniques have made major advances in reconstructing high-resolution images from low-resolution inputs. The increased resolution

Bias in Large Language Models: Origin, Evaluation, and Mitigation

arXiv:2411.10915v2 Announce Type: replace Abstract: Large Language Models (LLMs) have revolutionized natural language processing, but their susceptibility to biases poses significant challenges. This

safetyarxiv-cs-cl

Tutorials

Case Study: Accelerating AI from Prototype to Production with Metrum AI

This case study examines how Metrum AI leveraged Vultr's cloud infrastructure and services to accelerate the transition of AI projects from prototype to production environments. It likely covers the t

tutorialsvultr

Copula-enhanced Vision Transformer for high myopia diagnosis through OU UWF fundus images

arXiv:2501.06540v2 Announce Type: replace Abstract: The advancement of AI-assisted myopia screening necessitates the joint diagnosis of both-eye (OU) high myopia (HM) status and the prediction of axia

[D] What Happened to Neurips Creative AI Track? [R]

researchr-machinelearning

The NeurIPS Creative AI track became part of the main conference proceedings for 2025, with papers presented as posters during the conference , marking a change from 2024 when the track was not part o

Tutorials

Efficient Mutation Testing of Quantum Machine Learning Models

arXiv:2605.00107v1 Announce Type: cross Abstract: Quantum machine learning integrates the strengths of quantum computing and machine learning, enabling models to learn complex features using fewer par

tutorialsarxiv-cs-lg

EGREFINE: An Execution-Grounded Optimization Framework for Text-to-SQL Schema Refinement

arXiv:2605.00628v1 Announce Type: cross Abstract: Text-to-SQL enables non-expert users to query databases in natural language, yet real-world schemas often suffer from ambiguous, abbreviated, or incon

local-aiarxiv-cs-cl

Elimination Templates in Macaulay2

arXiv:2605.00278v1 Announce Type: cross Abstract: We introduce the package exttt{EliminationTemplates} for the Macaulay2 computer algebra system, which provides tools for constructing automatic solver

Event-based Civil Infrastructure Visual Defect Detection: ev-CIVIL Dataset and Benchmark

arXiv:2504.05679v2 Announce Type: replace Abstract: Small unmanned aerial vehicle (UAV)-based visual inspections are a more efficient alternative to manual methods for examining civil structural defec

Exploring the System 1 Thinking Capability of Large Reasoning Models

model-releasesarxiv-cs-cl

arXiv:2504.10368v4 Announce Type: replace Abstract: This paper explores the system 1 thinking capability of Large Reasoning Models (LRMs), the intuitive ability to respond efficiently with minimal tok

FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources

model-releasesarxiv-cs-lg

arXiv:2605.00011v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative intelligence across decentralized data source devices in a privacy-preserving way. While substantial resea

How General Intelligence used agents to build an agent platform on Vercel

General Intelligence built their agent platform using AI agents themselves, leveraging Vercel's infrastructure and deployment capabilities. The approach demonstrates how autonomous agents can be used

agentsvercel-blog

Instance-Aware Pseudo-Labeling and Class-Focused Contrastive Learning for Weakly Supervised Domain Adaptive Segmentation of Electron Microscopy

arXiv:2510.16450v2 Announce Type: replace Abstract: Annotation-efficient segmentation of the numerous mitochondria instances from various electron microscopy (EM) images is highly valuable for biologi

InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information

model-releasesarxiv-cs-cl

arXiv:2508.07630v2 Announce Type: replace Abstract: We introduce InterChart, a diagnostic benchmark that evaluates how well vision-language models (VLMs) reason across multiple related charts, a task

Introducing WARM-VR: Benchmark Dataset for Multimodal Wearable Affect Recognition in Virtual Reality

model-releasesarxiv-cs-lg

arXiv:2605.00184v1 Announce Type: new Abstract: With the growing integration of human-computer interaction into everyday life, advances in machine learning have enabled systems to better perceive and

Learn where to Click from Yourself: On-Policy Self-Distillation for GUI Grounding

arXiv:2605.00642v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding maps natural language instructions to the visual coordinates of target elements and serves as a core capabili

safetyarxiv-cs-cv

Lightweight Domain Adaptation of a Large Language Model for Legal Assistance in the Indian Context

model-releasesarxiv-cs-cl

arXiv:2505.22003v2 Announce Type: replace Abstract: In India, access to legal assistance for the general public has been observed to have a critical gap, as many citizens are not able to take full adv

Industry

Penske and Amazon introduce supply chain logistics solutions aimed at businesses

Amazon.com Inc. and Penske Logistics, the transportation solutions division of Penske Corp. Inc., today separately announced supply chain solutions aimed at easing business operations. Penske announce

industrysiliconangle

Prefer-DAS: Learning from Local Preferences and Sparse Prompts for Domain Adaptive Segmentation of Electron Microscopy

arXiv:2602.19423v3 Announce Type: replace Abstract: Domain adaptive segmentation (DAS) is a promising paradigm for delineating intracellular structures from various large-scale electron microscopy (EM

local-aiarxiv-cs-cv