Search: “automated”

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize

arXiv:2607.27389v1 Announce Type: new Abstract: Learning-to-optimize (L2O) methods accelerate repeated optimization by training models to predict solutions, warm starts, branching decisions, or other

researcharxiv-cs-lg

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation

DGX agent

arXiv:2506.21076v4 Announce Type: replace Abstract: Pose stylization, which aims to synthesize stylized content aligning with target poses, serves as a fundamental task across 2D, 3D, and video domain

safetyarxiv-cs-cv

31 Jul 2026

RadHarmony: Radiological Data Handling in the Era of Agentic AI

arXiv:2607.27235v1 Announce Type: cross Abstract: Training deep learning models on radiological images requires integrating heterogeneous datasets across different sources, file formats, directory lay

agentsarxiv-cs-cv

RepBench: Compiling Benchmarks into Capability Representations for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.28008v1 Announce Type: new Abstract: Representation engineering reads and steers capability directions in large language models, yet methods are typically evaluated on paper-specific synthe

State-Dependent Safety Failures in Multi-Turn Language Model Interaction

arXiv:2603.15684v2 Announce Type: replace-cross Abstract: Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although

Applications

Wiring diagram extraction and gluing: a case study in classifying figure skating jumps using 3D dataset

arXiv:2607.27598v1 Announce Type: cross Abstract: Hasse clustering is an algorithm that extracts common patterns in sequential data and represents them in graphical forms. As the number of expected cl

applicationsarxiv-cs-lg

AgentGUI: An Interface for Observing and Steering Long-Running AI Agents

arXiv:2607.26300v1 Announce Type: new Abstract: AI agents are increasingly adept at tackling complex, long-running tasks. With the rapid surge of autonomous capabilities, human oversight is systematic

local-aiarxiv-cs-cl

Controlled Experiments on Lane Changing by Transitional Autonomous Vehicle: Dataset and Behavioral Insights

arXiv:2607.27085v1 Announce Type: new Abstract: This paper presents the North Carolina Transitional Autonomous Vehicle Lane-Changing (NC-tALC) dataset and uses it to characterize mandatory lane-changi

safetyarxiv-cs-ro

Scientific Knowledge Discovery in the Age of Large Language Models

arXiv:2607.26670v1 Announce Type: cross Abstract: The rapid growth of scholarly literature has made identifying relevant publications increasingly difficult, and conventional search systems still depe

researcharxiv-cs-cl

Where Physics Meets Privacy: Federated PINNs for Privacy-Preserving Brain Tumor Biomechanical Modeling

arXiv:2607.26207v1 Announce Type: new Abstract: Brain tumors such as glioma, meningioma, and pituitary adenoma alter the mechanical behavior of soft brain tissue, yet common diagnostic methods rely on

local-aiarxiv-cs-cv

Balancing multiscale similarity and cartographic constraints: A similarity-driven optimization framework for line generalization

arXiv:2607.25474v1 Announce Type: new Abstract: Cartographic generalization is essential for generating multiscale map representations by balancing information preservation and cartographic readabilit

29 Jul 2026

CogEEGAgent: Toward Autonomous Cognitive EEG Analysis with Grounded Execution and Selection-Aware Verification

arXiv:2607.25045v1 Announce Type: new Abstract: Electroencephalography (EEG) analysis in cognitive studies requires specialized expertise and involves many defensible choices over contrasts, channels,

29 Jul 2026

ARdena: Scenario-driven control of real-time LLM agents

arXiv:2607.22651v1 Announce Type: new Abstract: Large language models (LLMs) have enabled increasingly capable conversational agents, but reliably controlling their behavior in real-time interactive e

AutoCluster, AutoTopicModeling, AutoTrendAnalysis: A Complete AutoML Pipeline for Predicting Emerging Trends

arXiv:2607.22641v1 Announce Type: cross Abstract: Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability.

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data

arXiv:2607.24717v1 Announce Type: cross Abstract: Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs). However, many existing approaches define a fixe

Designing Service Systems from Textual Evidence

arXiv:2603.10400v2 Announce Type: replace-cross Abstract: Designing service systems requires selecting among alternative configurations -- choosing the best chatbot variant, the optimal routing policy

Diffusion-Guided Search via Exponential Tilting (DiffTilt): An Application to Falsification of Safety-Critical Systems

arXiv:2607.23134v1 Announce Type: new Abstract: Discovering rare safety-critical failures in autonomous and cyber-physical systems is a fundamental challenge in verification and validation. Existing f

DualityCert: Verifier-Gated Language-Model Repair of Broken Duality Claims in Quantum Field Theory

arXiv:2607.23614v1 Announce Type: cross Abstract: We present DualityCert, a symbolic verifier for candidate Seiberg-duality claims in four-dimensional N=1 quiver gauge theories. The verifier evaluates

Flash-CNNCap: Capacitance Extraction via Image Mapping

arXiv:2607.23877v1 Announce Type: new Abstract: We present Flash-CNNCap, a CNN-based capacitance extractor that reformulates full-matrix capacitance prediction as image-to-image regression over spatia

MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents

arXiv:2607.18999v2 Announce Type: replace-cross Abstract: Evaluating multi-turn medical consultation agents requires judging the diagnostic support provided by the histories they elicit through intera

OS-Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows

arXiv:2510.24411v3 Announce Type: replace Abstract: Computer-using agents powered by Vision-Language Models (VLMs) have demonstrated human-like capabilities in operating digital environments like mobi

scMIR: a vision-language foundation model for single-cell light microscopy image representation

arXiv:2607.22712v1 Announce Type: cross Abstract: Single-cell light microscopy images have become an important data source for characterizing cell phenotypes, but their complexity and heterogeneity po

SIREN: Towards End-to-End Extreme-Weather Early Warning with Experience-Grounded LLM Agents

arXiv:2607.24588v1 Announce Type: new Abstract: Early warning of extreme weather is essential for mitigating the societal, economic, and environmental risks posed by hazardous weather events. However,

Synthetic Scenario Generation for Evaluation of Industry 4.0 Agents

arXiv:2607.22563v1 Announce Type: new Abstract: Industrial agent benchmarks require realistic evaluation scenarios that integrate telemetry, failure modes, maintenance records, and domain standards. H

Text-based Tactile Graphics Generation for the Visually Impaired

arXiv:2607.22674v1 Announce Type: cross Abstract: Tactile graphics are a primary medium for blind and low-vision (BLV) individuals to access non-textual information. However, they are difficult to sca

researcharxiv-cs-cv

Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents

arXiv:2606.13385v2 Announce Type: replace-cross Abstract: LLM-based web agents are increasingly deployed in real-world settings such as e-commerce, where they interact extensively with untrusted web c

CARE: Anti-entanglement Ultrasound Image Segmentation via Channel-Aware Region Extrication

arXiv:2508.13899v2 Announce Type: replace Abstract: Accurate ultrasound image segmentation is fundamentally challenged by target-context entanglement, where lesion cues are easily mixed with surroundi

researcharxiv-cs-cv

Medical-Checklist: Assessing the Comprehension of Medical Images by Multimodal Models

model-releasesarxiv-cs-cv

arXiv:2607.21998v1 Announce Type: new Abstract: This paper introduces a new benchmark test, Medical-Checklist, for assessing medical multimodal models. The recent advancements in multimodal models hav

Reliability Scales Inversely: Bigger Language Models Compound Mistakes Faster

arXiv:2607.18292v2 Announce Type: replace-cross Abstract: As language models scale, answers start truer but degrade faster: scaling buys capability but erodes reliability. The knowledge-gap account --

safetyarxiv-cs-cl

Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study

arXiv:2607.21866v1 Announce Type: new Abstract: Prior classical-ML learning-curve work fits power laws to tree, linear, and kernel models on tabular data, but at small scale: typically one curve, one

OPTScientist: Multi-Agent Discovery of Typed Optimizer Programs for Transformer Pretraining

arXiv:2607.20486v1 Announce Type: new Abstract: Designing optimizers for modern deep learning remains a challenging scientific problem, requiring the joint consideration of optimization geometry, stat

agentsarxiv-cs-ai

24 Jul 2026

The Human-AI Substitution Principle: When will you be replaced by AI in your organization?

arXiv:2607.20781v1 Announce Type: new Abstract: Artificial Intelligence (AI) is rapidly transforming organizations, raising a fundamental organizational and economic question: when will a human employ

24 Jul 2026

CreatiPoster: Towards Editable and Controllable Multi-Layer Graphic Design Generation

model-releasesarxiv-cs-cv

arXiv:2506.10890v2 Announce Type: replace Abstract: Graphic design plays a crucial role in both commercial and personal contexts, yet creating high-quality, editable, and aesthetically pleasing graphi

23 Jul 2026

Hypothesis-and-Refinement Learning of Organic Structures from Multimodal Spectroscopic Data

arXiv:2607.19816v1 Announce Type: cross Abstract: Determining molecular structures from spectroscopic data remains fundamentally challenging because the inverse problem is intrinsically underdetermine

23 Jul 2026

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System

arXiv:2607.13608v1 Announce Type: new Abstract: Automatic scientific discovery has long been a goal of computational scholars - a machine that can discover nature's secrets on its own, moving computat

agentsarxiv-cs-ai

Faithful Autoformalization of Natural Language Assertions

arXiv:2607.13303v1 Announce Type: cross Abstract: Formal contracts are essential for software testing and verification, yet writing them remains labor-intensive and error-prone. LLMs offer a promising

Reverse to Advance: Teleoperation-Cost Effective Hard Policy Learning from Reversed Easy Tasks

arXiv:2607.13455v1 Announce Type: new Abstract: High-quality teleoperation datasets are costly to collect, particularly for hard tasks. We observe that many tasks exhibit directional asymmetry: comple

safetyarxiv-cs-ro

Self-Improving AI Coding Agents Through Accumulated Behavioral Rules: A Closed-Loop Framework

arXiv:2607.13091v1 Announce Type: cross Abstract: LLM-based coding agents repeat the same classes of mistakes across sessions because they lack a mechanism to retain corrections from human review feed

agentsarxiv-cs-ai

A Neurosymbolic Approach to Natural Language Formalization and Verification

arXiv:2511.09008v2 Announce Type: replace-cross Abstract: Large Language Models perform well at natural language interpretation and reasoning, but their lack of formal correctness guarantees limits th

Agentic systems for breast cancer treatment recommendations

model-releasesarxiv-cs-cl

arXiv:2607.12051v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical decision support, but their reliability in complex oncology treatment planning

CrochetBench: Can Vision-Language Models Move from Describing to Doing in Crochet Domain?

arXiv:2511.09483v3 Announce Type: replace Abstract: While multimodal large language models can describe visual content, their ability to generate executable procedures remains underexplored. CrochetBe

Good Benchmarks

arXiv:2607.12217v1 Announce Type: new Abstract: Good tasks are correct, solvable, verifiable, well-specified, and hard for interesting reasons. The best tasks describe a real problem an experienced pr

How Inference Compute Shapes Frontier LLM Evaluation

arXiv:2606.17930v2 Announce Type: replace Abstract: AI evaluations are shifting toward harder tasks that benefit from longer trajectories involving tool use and iterative problem solving. As a result,

M2I2HA: Multi-modal Object Detection Based on Intra- and Inter-Modal Hypergraph Attention

arXiv:2601.14776v3 Announce Type: replace Abstract: Recent advances in multi-modal detection have significantly improved detection accuracy in challenging environments (e.g., low light, overexposure).

safetyarxiv-cs-cv

Same Loss, Same Noise, Opposite Schedules: Noise Structure and Optimizer Normalization Jointly Determine Whether Learning-Rate Cooldown Helps

arXiv:2607.12360v1 Announce Type: new Abstract: The cooldown phase of a warmup-stable-decay (WSD) learning-rate schedule, now a default in large-model pretraining, lowers the final training loss in so

researcharxiv-cs-lg

SeqGPT: A Constrained Transformer Agent for the Inverse Designof Multi-Panel Composite Structures

arXiv:2607.11910v1 Announce Type: cross Abstract: Optimizing composite stacking sequences to match continuous targets (e.g., Lamination or Buckling Parameters) with discrete manufacturing constraints

WanToFight: Real-Time Generative Game Engine for Multi-Player Combat Interaction

arXiv:2607.12592v1 Announce Type: new Abstract: We present WanToFight, a generative game engine that simulates real-time, two-player The King of Fighters '97 (KOF~'97) gameplay from keyboard input. Pr

local-aiarxiv-cs-cv

FPGN: Redefining Ultra-Fast Programmable Gate-based Neural Acceleration with Differentiable LUTs