Search: “applications”

DharmaOCR: Specialized Small Language Models for Structured OCR that outperform Open-Source and Commercial Baselines

model-releasesarxiv-cs-cl

arXiv:2604.14314v1 Announce Type: cross Abstract: This manuscript introduces DharmaOCR Full and Lite, a pair of specialized small language models (SSLMs) for structured OCR that jointly optimize trans

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Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach

DGX agent

arXiv:2411.00361v4 Announce Type: replace Abstract: Hierarchical reinforcement learning (HRL) enables agents to solve complex, long-horizon tasks by decomposing them into manageable sub-tasks. However

safetyarxiv-cs-lg

17 Apr 2026

Tools

Download Cursor to use the agents window: http://cursor.com/download

Cursor is an AI-powered code editor that offers a download option for users to access the agents window feature. The agents window allows developers to leverage AI capabilities within the Cursor envir

toolscursor--x

Efficient closed-form approaches for pose estimation using Sylvester forms

arXiv:2604.14747v1 Announce Type: new Abstract: Solving non-linear least-squares problem for pose estimation (rotation and translation) is often a time consuming yet fundamental problem in several rea

Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design

arXiv:2512.24120v2 Announce Type: replace Abstract: Automated neural network architecture design remains a significant challenge in computer vision. Task diversity and computational constraints requir

Everyone’s quitting but everything’s going great. AGI will be here next week. Scout’s honor!

Everyone’s quitting but everything’s going great. AGI will be here next week. Scout’s honor! This story has now been updated with more details. Three leaders departed from OpenAI today: - Kevin Weil,

safetygary-marcus--x

Exploiting Correlations in Federated Learning: Opportunities and Practical Limitations

model-releasesarxiv-cs-lg

arXiv:2604.14751v1 Announce Type: cross Abstract: The communication bottleneck in federated learning (FL) has spurred extensive research into techniques to reduce the volume of data exchanged between

Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure Generation

arXiv:2604.13354v1 Announce Type: cross Abstract: The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially

researcharxiv-cs-ai

Flux Dev.1 Artistic Mix 04-16-2026

local-air-stablediffusion

Flux Dev is a higher-quality variant of the Flux.1 image generation model that is non-commercial . The Reddit post titled 'Flux Dev.1 Artistic Mix 04-16-2026' likely showcases a community member's cur

Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems

arXiv:2510.14133v2 Announce Type: replace Abstract: Agentic AI systems, which leverage multiple autonomous agents and large language models (LLMs), are increasingly used to address complex, multi-step

safetyarxiv-cs-ai

Generative Augmented Inference

arXiv:2604.14575v1 Announce Type: new Abstract: Data-driven operations management often relies on parameters estimated from costly human-generated labels. Recent advances in large language models (LLM

Generative Modeling of Complex-Valued Brain MRI Data

arXiv:2604.14800v1 Announce Type: cross Abstract: Objective. Standard Magnetic Resonance Imaging (MRI) reconstruction pipelines discard phase information captured during acquisition, despite evidence

Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI

arXiv:2403.10559v3 Announce Type: replace Abstract: This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing

safetyarxiv-cs-lg

Graph-Based Alternatives to LLMs for Human Simulation

arXiv:2511.02135v2 Announce Type: replace Abstract: Large language models (LLMs) have become a popular approach for simulating human behaviors, yet it remains unclear if LLMs are necessary for all sim

researcharxiv-cs-cl

High Probability Guarantees for Random Reshuffling

arXiv:2311.11841v4 Announce Type: replace-cross Abstract: We consider the stochastic gradient method with random reshuffling (mathsf{RR}) for tackling smooth nonconvex optimization problems. mathsf{RR

Tools

How Zo Computer improved AI reliability 20x on Vercel

Zo Computer achieved a 20-fold improvement in AI reliability by leveraging Vercel's infrastructure and deployment capabilities. The optimization likely involved implementing better error handling, red

toolsvercel-blog

Implicit Neural Representations: A Signal Processing Perspective

arXiv:2604.15047v1 Announce Type: new Abstract: Implicit neural representations (INRs) mark a fundamental shift in signal modeling, moving from discrete sampled data to continuous functional represent

safetyarxiv-cs-cv

Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making

arXiv:2604.14240v1 Announce Type: cross Abstract: The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models p

agentsarxiv-cs-lg

IROSA: Interactive Robot Skill Adaptation using Natural Language

arXiv:2603.03897v3 Announce Type: replace-cross Abstract: Foundation models have demonstrated impressive capabilities across diverse domains, while imitation learning provides principled methods for r

JoyVASA: Portrait and Animal Image Animation with Diffusion-Based Audio-Driven Facial Dynamics and Head Motion Generation

arXiv:2411.09209v5 Announce Type: replace Abstract: Audio-driven portrait animation has made significant advances with diffusion-based models, improving video quality and lipsync accuracy. However, th

Keep It CALM: Toward Calibration-Free Kilometer-Level SLAM with Visual Geometry Foundation Models via an Assistant Eye

arXiv:2604.14795v1 Announce Type: new Abstract: Visual Geometry Foundation Models (VGFMs) demonstrate remarkable zero-shot capabilities in local reconstruction. However, deploying them for kilometer-l

local-aiarxiv-cs-ro

Industry

Kevin Weil, OpenAI's former CPO who became VP of OpenAI for Science, is leaving the company; Prism, a web app for scientists launched in Jan., will be shuttered (Maxwell Zeff/Wired)

Maxwell Zeff / Wired: Kevin Weil, OpenAI's former CPO who became VP of OpenAI for Science, is leaving the company; Prism, a web app for scientists launched in Jan., will be shuttered — The former Inst

industrytechmeme

Learning Adaptive Reasoning Paths for Efficient Visual Reasoning

arXiv:2604.14568v1 Announce Type: cross Abstract: Visual reasoning models (VRMs) have recently shown strong cross-modal reasoning capabilities by integrating visual perception with language reasoning.

Tutorials

Learning to Plan, Planning to Learn: Adaptive Hierarchical RL-MPC for Sample-Efficient Decision Making

arXiv:2512.17091v2 Announce Type: replace Abstract: We propose a new approach for solving planning problems with a hierarchical structure, fusing reinforcement learning and MPC planning. Our formulati

tutorialsarxiv-cs-lg

MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents

model-releasesarxiv-cs-ai

arXiv:2509.06477v2 Announce Type: replace Abstract: Shortcuts such as APIs and deep-links have emerged as efficient complements to flexible GUI operations, fostering a promising hybrid paradigm for ML

MIND: AI Co-Scientist for Material Research

arXiv:2604.13699v1 Announce Type: cross Abstract: Large language models (LLMs) have enabled agentic AI systems for scientific discovery, but most approaches remain limited to textbased reasoning witho

agentsarxiv-cs-ai

ML-based approach to classification and generation of structured light propagation in turbulent media

arXiv:2604.14208v1 Announce Type: cross Abstract: This work develops machine learning approaches to classify structured light wave beams developing random speckle disturbances as they propagate throug

Industry

NanoClaw partners with Vercel to deliver one-click approvals for AI agents working on sensitive tasks

NanoCo, the startup behind NanoClaw, a fast-growing alternative to OpenAI Group PBC’s OpenClaw project, said today it’s teaming up with Vercel Inc. and OneCLI to try to fix the “trust problem” holding

industrysiliconangle

One-shot learning for the complex dynamical behaviors of weakly nonlinear forced oscillators

arXiv:2604.15181v1 Announce Type: new Abstract: Extrapolative prediction of complex nonlinear dynamics remains a central challenge in engineering. This study proposes a one-shot learning method to ide

agentsarxiv-cs-lg

POMDP-based Object Search with Growing State Space and Hybrid Action Domain

arXiv:2604.14965v1 Announce Type: new Abstract: Efficiently locating target objects in complex indoor environments with diverse furniture, such as shelves, tables, and beds, is a significant challenge

local-aiarxiv-cs-ro

Predictions of charge density distributions for nuclei with Z geq 8

arXiv:2604.05312v1 Announce Type: cross Abstract: A deep neural network (DNN) has been developed to accurately predict nuclear charge density distributions for nuclei with proton numbers Z geq 8. By i

ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration

arXiv:2509.21823v2 Announce Type: replace Abstract: Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods strugg

safetyarxiv-cs-ai

Regret Tail Characterization of Optimal Bandit Algorithms with Generic Rewards

model-releasesarxiv-cs-lg

arXiv:2604.14876v1 Announce Type: cross Abstract: We study the tail behavior of regret in stochastic multi-armed bandits for algorithms that are asymptotically optimal in expectation. While minimizing

RL-STPA: Adapting System-Theoretic Hazard Analysis for Safety-Critical Reinforcement Learning

arXiv:2604.15201v1 Announce Type: new Abstract: As reinforcement learning (RL) deployments expand into safety-critical domains, existing evaluation methods fail to systematically identify hazards aris

safetyarxiv-cs-lg

Robustness of Vision Foundation Models to Common Perturbations

arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright

RoSLAC: Robust Simultaneous Localization and Calibration of Multiple Magnetometers

arXiv:2604.14353v1 Announce Type: new Abstract: Localization of autonomous mobile robots (AMRs) in enclosed or semi-enclosed environments such as offices, hotels, hospitals, indoor parking facilities,

safetyarxiv-cs-ro

SAGE: Sign-Adaptive Gradient for Memory-Efficient LLM Optimization

model-releasesarxiv-cs-lg

arXiv:2604.07663v2 Announce Type: replace Abstract: The AdamW optimizer, while standard for LLM pretraining, is a critical memory bottleneck, consuming optimizer states equivalent to twice the model's

SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMs

arXiv:2602.13529v2 Announce Type: replace-cross Abstract: Federated learning (FL) enables collaborative training across organizational silos without sharing raw data, making it attractive for privacy-

local-aiarxiv-cs-cl

Shared Dictionaries: compression that keeps up with the agentic web

Shared Dictionaries is a web compression technology developed by Cloudflare that enables more efficient data transmission by allowing browsers and servers to reference common dictionary files rather t

agentscloudflare-ai

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models

arXiv:2604.14672v1 Announce Type: new Abstract: Large language models (LLMs) are being increasingly used in urban planning, but since gendered space theory highlights how gender hierarchies are embedd

Structural interpretability in SVMs with truncated orthogonal polynomial kernels

arXiv:2604.15285v1 Announce Type: cross Abstract: We study post-training interpretability for Support Vector Machines (SVMs) built from truncated orthogonal polynomial kernels. Since the associated re

Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging

arXiv:2410.08329v3 Announce Type: replace Abstract: Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse t

The Acoustic Camouflage Phenomenon: Re-evaluating Speech Features for Financial Risk Prediction

arXiv:2604.14619v1 Announce Type: cross Abstract: In computational paralinguistics, detecting cognitive load and deception from speech signals is a heavily researched domain. Recent efforts have attem

Industry

The Inference Cloud Memory Layer: A Technical Dive into DigitalOcean Managed Databases

DigitalOcean's Inference Cloud Memory Layer is a technical architecture component designed to optimize database performance by implementing an in-memory caching layer for faster data access and reduce

industrydigitalocean

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure

arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp

Tight Bounds for Learning Polyhedra with a Margin

arXiv:2604.14614v1 Announce Type: cross Abstract: We give an algorithm for PAC learning intersections of k halfspaces with a rho margin to within error arepsilon that runs in time extsf{poly}(k, areps

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions

arXiv:2604.14398v1 Announce Type: cross Abstract: Rotating detonation engines (RDEs) are a promising propulsion concept that may offer higher thermodynamic efficiency and specific impulse than convent

agentsarxiv-cs-lg

Uncovering the Fragility of Trustworthy LLMs through Chinese Textual Ambiguity

model-releasesarxiv-cs-cl

arXiv:2507.23121v2 Announce Type: replace Abstract: In this work, we study a critical research problem regarding the trustworthiness of large language models (LLMs): how LLMs behave when encountering