Search: “applications”

Co-Generative De Novo Functional Protein Design

arXiv:2605.00948v1 Announce Type: cross Abstract: De novo functional protein design aims to generate protein sequences that realize specified biochemical functions without relying on evolutionary temp

researcharxiv-cs-ai

Disease Is a Spectral Perturbation

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arXiv:2605.02949v1 Announce Type: new Abstract: We propose a novel method of understanding disease transformation from a healthy baseline with biomarker-level explainability. By modeling the biomarker

researcharxiv-cs-lg

6 May 2026

Industry

Elon Musk: 'I'm actually quite a big fan of tunnels. Tunnels are so under-appreciated.'

Elon Musk expressed enthusiasm for tunnel infrastructure, emphasizing that tunnels are undervalued in transportation and urban planning. This statement aligns with his broader work through The Boring

industryelon-musk--x

EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions

arXiv:2605.02289v1 Announce Type: new Abstract: Engineering problem solving is central to real-world decision-making, requiring mathematical formulations that not only represent complex problems but a

agentsarxiv-cs-ai

Evaluating Generative Models as Interactive Emergent Representations of Human-Like Collaborative Behavior

arXiv:2605.03855v1 Announce Type: new Abstract: Human-AI collaboration requires AI agents to understand human behavior for effective coordination. While advances in foundation models show promising ca

researcharxiv-cs-ro

FINER-SQL: Boosting Small Language Models for Text-to-SQL

arXiv:2605.03465v1 Announce Type: cross Abstract: Large language models have driven major advances in Text-to-SQL generation. However, they suffer from high computational cost, long latency, and data

safetyarxiv-cs-cl

Flow Matching on Symmetric Spaces

arXiv:2605.03588v1 Announce Type: new Abstract: We introduce a general framework for training flow matching models on Riemannian symmetric spaces, a large class of manifolds that includes the sphere,

From SFT to RL: Demystifying the Post-Training Pipeline for LLM-based Vulnerability Detection

arXiv:2602.14012v2 Announce Type: replace-cross Abstract: The integration of LLMs into vulnerability detection (VD) has shifted the field toward more interpretable and context-aware analysis. While po

safetyarxiv-cs-ai

GeoTopoDiff: Learning Geometry--Topology Graph Priors through Boundary-Constrained Mixed Diffusion for Sparse-Slice 3D Porous Reconstruction

arXiv:2605.03764v1 Announce Type: new Abstract: Diffusion-based voxel prior modelling is challenging for the reconstruction of large-scale 3D porous microstructures. Due to the demanding requirements

Local Ai

How can Anima work on StabilityMatrix?

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Anima is a 2 billion parameter text-to-image model created via collaboration between CircleStone Labs and Comfy Org , while Stability Matrix is a multi-platform package manager that serves as a wrappe

Hybrid Inspection and Task-Based Access Control in Zero-Trust Agentic AI

arXiv:2605.02682v1 Announce Type: new Abstract: Authorizing Large Language Model (LLM)-driven agents to dynamically invoke tools and access protected resources introduces significant security risks, a

agentsarxiv-cs-ai

Large-Scale High-Quality 3D Gaussian Head Reconstruction from Multi-View Captures

arXiv:2605.04035v1 Announce Type: new Abstract: We propose HeadsUp, a scalable feed-forward method for reconstructing high-quality 3D Gaussian heads from large-scale multi-camera setups. Our method em

Latent State Design for World Models under Sufficiency Constraints

arXiv:2605.01694v1 Announce Type: new Abstract: A world model matters to an agent only through the state it constructs. That state must preserve some information, discard other information, and suppor

agentsarxiv-cs-ai

Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective

arXiv:2605.03373v1 Announce Type: new Abstract: Classical optimization theory establishes that zeroth-order (ZO) algorithms suffer from a dimension-dependent slowdown, with convergence rates typically

Learning Generalizable Action Representations via Pre-training AEMG

arXiv:2605.03462v1 Announce Type: new Abstract: A fundamental role in decoding human motor intent and enabling intuitive human-computer interaction is played by electromyography (EMG). However, its ge

Hardware

Learning Zero-Shot Subject-Driven Video Generation Using 1% Compute

arXiv:2504.17816v3 Announce Type: replace Abstract: Subject-driven video generation (SDV-Gen) aims to produce videos of a specific subject by adapting a pretrained video model, enabling personalized a

hardwarearxiv-cs-cv

Local Ai

Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting

arXiv:2605.03386v1 Announce Type: new Abstract: Spatiotemporal forecasting in physical systems, such as large-scale traffic networks, requires modeling a dual dynamic: continuous macroscopic rhythms a

local-aiarxiv-cs-lg

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach

arXiv:2511.01680v3 Announce Type: replace-cross Abstract: Social scientists are increasingly turning to unstructured datasets to unlock new empirical insights, e.g., estimating descriptive statistics

Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations

arXiv:2605.03511v1 Announce Type: new Abstract: Solving inverse problems in dynamical systems governed by high-dimensional coupled ordinary differential equations (ODEs) is a ubiquitous challenge in s

Metadata, Wavelet, and Time Aware Diffusion Models for Satellite Image Super Resolution

arXiv:2506.23566v2 Announce Type: replace Abstract: The acquisition of high-resolution satellite imagery is often constrained by the spatial and temporal limitations of satellite sensors, as well as t

Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling

arXiv:2605.01566v1 Announce Type: new Abstract: Advances in inference methods have enabled language models to improve their predictions without additional training. These methods often prioritize raw

Neuro-Symbolic Agents for Hallucination-Free Requirements Reuse

arXiv:2605.01562v1 Announce Type: cross Abstract: The Object-Oriented Method for Requirements Authoring and Management (OOMRAM) is a requirements reuse framework that relies on exact identifier matchi

NEURON: A Neuro-symbolic System for Grounded Clinical Explainability

arXiv:2605.01189v1 Announce Type: new Abstract: Clinical AI adoption is hindered by the black-box/grey-box nature of high-performing models, which lack the ontological grounding and narrative transpar

researcharxiv-cs-ai

On the Spectral Structure and Objective Equivalence of Orthogonal Multilabel Fisher Discriminants

arXiv:2605.03283v1 Announce Type: cross Abstract: We provide a unified theoretical analysis of Linear Discriminant Analysis with simultaneous multilabel scatter matrix formulations and Stiefel orthogo

Position: How can Graphs Help Large Language Models?

arXiv:2605.02452v1 Announce Type: new Abstract: With the rapid advancement of large language models (LLMs), classic graph learning tasks have greatly benefited from LLMs, including improved encoding o

researcharxiv-cs-ai

Predicting Euler Characteristics and Constructing Topological Structure Using Machine Learning Techniques

arXiv:2605.02947v1 Announce Type: new Abstract: This study proposes a novel approach to extract topological properties, specifically the Euler characteristic, from input images using neural networks w

Pseudo-differential-enhanced physics-informed neural networks

arXiv:2602.14663v2 Announce Type: replace Abstract: We present pseudo-differential enhanced physics-informed neural networks (PINNs), an extension of gradient enhancement but in Fourier space. Gradien

safetyarxiv-cs-lg

Reservoir property image slices from the Groningen gas field for image translation and segmentation

arXiv:2605.03942v1 Announce Type: new Abstract: Reservoir characterization workflows increasingly rely on image-based and machine-learning/deep learning or even generative AI approaches, but openly av

Resource-Efficient Reinforcement for Reasoning Large Language Models via Dynamic One-Shot Policy Refinement

arXiv:2602.00815v2 Announce Type: replace Abstract: Large language models (LLMs) have exhibited remarkable performance on complex reasoning tasks, with reinforcement learning under verifiable rewards

safetyarxiv-cs-ai

Industry

Rethinking Distributed Systems for Serverless Performance and Reliability

This Databricks article examines how distributed systems architectures need to be redesigned for serverless computing environments, addressing the unique performance and reliability challenges that ar

industrydatabricks

Robust Language Identification for Romansh Varieties

model-releasesarxiv-cs-cl

arXiv:2603.15969v2 Announce Type: replace Abstract: The Romansh language has several regional varieties, called idioms, which sometimes have limited mutual intelligibility. Despite this linguistic div

Scoring Edit Impact in Grammatical Error Correction via Embedded Association Graphs

arXiv:2604.06573v2 Announce Type: replace Abstract: A Grammatical Error Correction (GEC) system produces a sequence of edits to correct an erroneous sentence. The quality of these edits is typically e

researcharxiv-cs-cl

Seeking Information with RAG-Assistants: Does Model Size Matter in Human-AI Collaborations?

arXiv:2605.00964v1 Announce Type: cross Abstract: Much research on LLMs has focused on increasing benchmark performance. However, the evaluation of such models in real-world collaborative human-AI wor

Singular Bank helps bankers move fast with ChatGPT and Codex

Singular Bank leverages OpenAI's ChatGPT and Codex to accelerate banking operations and developer productivity. The integration enables bankers and software engineers to streamline workflows, automate

model-releasesopenai

Structured Diffusion Bridges: Inductive Bias for Denoising Diffusion Bridges

arXiv:2605.02973v1 Announce Type: new Abstract: Modality translation is inherently under-constrained, as multiple cross-modal mappings may yield the same marginals. Recent work has shown that diffusio

safetyarxiv-cs-lg

Toggling stiffness via multistability

arXiv:2510.09511v2 Announce Type: replace-cross Abstract: Variable stiffness is a key capability in biological and robotic systems, enabling adaptive interaction across tasks and environments. Mechani

researcharxiv-cs-ro

Towards accurate extreme event likelihoods from diffusion model climate emulators

arXiv:2605.03802v1 Announce Type: cross Abstract: ML climate model emulators are useful for scenario planning and adaptation, allowing for cost-efficient experimentation. Recently, the diffusion model

Training-Free Probabilistic Time-Series Forecasting with Conformal Seasonal Pools

arXiv:2605.03789v1 Announce Type: cross Abstract: We propose Conformal Seasonal Pools (CSP), a training-free probabilistic time-series forecaster that mixes same-season empirical draws with signed res

Local Ai

Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers

arXiv:2605.03614v1 Announce Type: new Abstract: Visual affordances identify regions in an image with potential interactions, offering a novel paradigm for scene understanding. Recognizing affordances

local-aiarxiv-cs-cv

Valley3: Scaling Omni Foundation Models for E-commerce

arXiv:2605.01278v1 Announce Type: new Abstract: In this work, we present Valley3, an omni multimodal large language model (MLLM) developed for diverse global e-commerce tasks, with unified understandi

Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms

arXiv:2603.28489v2 Announce Type: cross Abstract: The rapid evolution of video generation has enabled models to simulate complex physical dynamics and long-horizon causalities, positioning them as pot

agentsarxiv-cs-cv

What's new in IAM: Security, governance, and runtime defense

model-releasesgoogle-cloud-ai

The AI era demands a fundamental shift in security, and that includes identity and access management (IAM). Traditional controls simply aren’t built for autonomous AI agents that interact with sensiti

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach

arXiv:2510.08952v4 Announce Type: replace Abstract: Text-attributed graphs (TAGs) have become a key form of graph-structured data in modern data management and analytics, combining structural relation

agentsarxiv-cs-lg

2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing

arXiv:2605.00839v1 Announce Type: cross Abstract: The evolution of artificial intelligence (AI) and machine learning (ML) is reshaping smart manufacturing by providing new capabilities for efficiency,

agentsarxiv-cs-lg

2D-ThermAl: Physics-Informed Framework for Thermal Analysis of Circuits using Generative AI

arXiv:2512.01163v2 Announce Type: replace Abstract: Thermal analysis is increasingly critical in modern integrated circuits, where non-uniform power dissipation and high transistor densities can cause

Industry

5.5 in codex is so good for non-coding tasks. i keep assuming it won't be able to do something, but a lot of the time i am pleasantly surpri…

Sam Altman notes that GPT-4.5 in Codex demonstrates strong performance on non-coding tasks, often exceeding expectations despite assumptions about its limitations. He highlights pleasant surprises in

industrysam-altman--x

A Hybrid Windkessel-Neural Approach for Improved Noninvasive Blood Pressure Monitoring

arXiv:2605.00858v1 Announce Type: cross Abstract: Owing to the recent advancements in wearable devices for health care, the importance of BP estimation without cuffs increases. Cuff technologies are i

Tutorials

A Survey of Reasoning-Intensive Retrieval: Progress and Challenges

arXiv:2605.00063v1 Announce Type: cross Abstract: Reasoning-Intensive Retrieval (RIR) targets retrieval settings where relevance is mediated by latent inferential links between a query and supporting

tutorialsarxiv-cs-ai