Search: “automated”

Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge

arXiv:2604.11679v1 Announce Type: new Abstract: Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are

researcharxiv-cs-cv

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Tuning Qwen2.5-VL to Improve Its Web Interaction Skills

DGX agent

arXiv:2604.09571v1 Announce Type: cross Abstract: Recent advances in vision-language models (VLMs) have sparked growing interest in using them to automate web tasks, yet their feasibility as independe

model-releasesarxiv-cs-ai

14 Apr 2026

Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation

arXiv:2604.10823v1 Announce Type: new Abstract: Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate bac

researcharxiv-cs-cv

VeriInteresting: An Empirical Study of Model Prompt Interactions in Verilog Code Generation

model-releasesarxiv-cs-cl

arXiv:2603.08715v2 Announce Type: replace-cross Abstract: Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between mod

WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance

model-releasesarxiv-cs-cv

arXiv:2604.10797v1 Announce Type: new Abstract: We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulti

AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs

arXiv:2604.08590v1 Announce Type: cross Abstract: We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full experimental cycle in quanti

Characterizing Lidar Range-Measurement Ambiguity due to Multiple Returns

arXiv:2604.09282v1 Announce Type: cross Abstract: Reliable position and attitude sensing is critical for highly automated vehicles that operate on conventional roadways. Lidar sensors are increasingly

researcharxiv-cs-cv

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning

arXiv:2507.04736v2 Announce Type: replace Abstract: Large Language Models have emerged as powerful tools for automating Register-Transfer Level (RTL) code generation, yet they face critical limitation

safetyarxiv-cs-ai

GeoPAS: Geometric Probing for Algorithm Selection in Continuous Black-Box Optimisation

model-releasesarxiv-cs-lg

arXiv:2604.09095v1 Announce Type: new Abstract: Automated algorithm selection in continuous black-box optimisation typically relies on fixed landscape descriptors computed under a limited probing budg

Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory

arXiv:2604.08995v1 Announce Type: new Abstract: With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, existing

applicationsarxiv-cs-cv

ReplicatorBench: Benchmarking LLM Agents for Replicability in Social and Behavioral Sciences

arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on

Adaptive Prompt Structure Factorization: A Framework for Self-Discovering and Optimizing Compositional Prompt Programs

arXiv:2604.06699v1 Announce Type: cross Abstract: Automated prompt optimization is crucial for eliciting reliable reasoning from large language models (LLMs), yet most API-only prompt optimizers itera

researcharxiv-cs-lg

Are Face Embeddings Compatible Across Deep Neural Network Models?

arXiv:2604.07282v1 Announce Type: cross Abstract: Automated face recognition has made rapid strides over the past decade due to the unprecedented rise of deep neural network (DNN) models that can be t

safetyarxiv-cs-lg

ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces

arXiv:2604.05172v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evalu

Local Ai

EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration

arXiv:2604.07003v1 Announce Type: new Abstract: Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in pri

local-aiarxiv-cs-ai

EvoGymCM: Harnessing Continuous Material Stiffness for Soft Robot Co-Design

model-releasesarxiv-cs-ro

arXiv:2604.08258v1 Announce Type: new Abstract: In the automated co-design of soft robots, precisely adapting the material stiffness field to task environments is crucial for unlocking their full phys

Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning

arXiv:2603.02070v2 Announce Type: replace-cross Abstract: When automating plan generation for a real-world sequential decision problem, the goal is often not to replace the human planner, but to facil

agentsarxiv-cs-cl

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning

arXiv:2604.06262v1 Announce Type: cross Abstract: Contextual clinical reasoning demands robust inference grounded in complex, heterogeneous clinical records. While state-of-the-art fine-tuning, in-con

researcharxiv-cs-ai

Harf-Speech: A Clinically Aligned Framework for Arabic Phoneme-Level Speech Assessment

arXiv:2604.06191v1 Announce Type: cross Abstract: Automated phoneme-level pronunciation assessment is vital for scalable speech therapy and language learning, yet validated tools for Arabic remain sca

Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Colored Point Clouds

arXiv:2411.07799v3 Announce Type: replace Abstract: Accurate and consistent fruit monitoring over time is a key step toward automated agricultural production systems. However, this task is inherently

applicationsarxiv-cs-cv

MAT-Cell: A Multi-Agent Tree-Structured Reasoning Framework for Batch-Level Single-Cell Annotation

arXiv:2604.06269v1 Announce Type: cross Abstract: Automated cellular reasoning faces a core dichotomy: supervised methods fall into the Reference Trap and fail to generalize to out-of-distribution cel

ORACLE-SWE: Quantifying the Contribution of Oracle Information Signals on SWE Agents

arXiv:2604.07789v1 Announce Type: cross Abstract: Recent advances in language model (LM) agents have significantly improved automated software engineering (SWE). Prior work has proposed various agenti

agentsarxiv-cs-cl

The Impact of Steering Large Language Models with Persona Vectors in Educational Applications

arXiv:2604.07102v1 Announce Type: cross Abstract: Activation-based steering can personalize large language models at inference time, but its effects in educational settings remain unclear. We study pe

'Why This Avoidance Maneuver?' Contrastive Explanations in Human-Supervised Maritime Autonomous Navigation

arXiv:2604.08032v1 Announce Type: cross Abstract: Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system p

agentsarxiv-cs-ro

DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation

arXiv:2507.14267v2 Announce Type: replace Abstract: Large language model (LLM) agents can execute long-horizon scientific workflows, but their numerical outputs are difficult to trust: agents lose con

13 Aug 2026

LLMs in Process Diagram Engineering: From Optimal PFDs to Validated P&IDs

arXiv:2608.11220v1 Announce Type: new Abstract: Nowadays, the creation of a process flow diagram (PFD) and its subsequent transformation into a piping and instrumentation diagram (P&ID) is predominant

13 Aug 2026

Actions Speak Louder than Words: Measuring Cross-Lingual Policy Retention in Tool-Using Agents

arXiv:2608.11110v1 Announce Type: new Abstract: When a tool-using agent is given the same task in a different language, does it still take the same steps? Multilingual evaluation rarely asks: it compa

safetyarxiv-cs-cl

Local Ai

Beyond Detection: Evaluating Defensive LLMs Against AI-Generated Social Engineering in Live Turn-by-Turn Interaction

arXiv:2608.10239v1 Announce Type: new Abstract: Generative AI makes social-engineering attacks more fluent, adaptive, and scalable, increasing the need for LLM-based de- fenders that can protect users

local-aiarxiv-cs-ai

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

arXiv:2608.10299v1 Announce Type: new Abstract: Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, s

agentsarxiv-cs-cl

Hardware

EvoMem: Memory-Augmented Evolution for Code Optimization

arXiv:2608.10795v1 Announce Type: new Abstract: Successful mutation strategies in evolutionary code search may contain reusable knowledge that is useful beyond a single run, and in some cases may tran

hardwarearxiv-cs-ai

Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach

arXiv:2602.16481v2 Announce Type: replace Abstract: Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of

safetyarxiv-cs-ai

Multilingual Embedding Probes Fail to Generalize Across Learner Corpora

arXiv:2604.07095v2 Announce Type: replace Abstract: Do multilingual embedding models encode a language-general representation of proficiency? We investigate this by training linear and non-linear prob

researcharxiv-cs-cl

Nutrition Data Infrastructure for the AI Era: Operationalizing FAIR for Agent-Mediated Research

arXiv:2608.10363v1 Announce Type: new Abstract: AI agents can accelerate nutrition research, but their analyses inherit the identity, semantic, and release ambiguities of the underlying data. We prese

On Solomonoff Induction in Large Language Models and the Limits of Self-Improving: The Singularity Is Not Near Without Symbolic Model Synthesis

arXiv:2601.05280v3 Announce Type: replace-cross Abstract: On the one hand, the question of whether large language models (LLMs) are Solomonoff induction estimators has become an explicit question at t

Persistent Recursive Worlds Enable Autonomous Software Evolution

arXiv:2608.10450v1 Announce Type: cross Abstract: Complex software systems develop over timescales that exceed the lifespan of any individual coding agent. Most agentic software systems preserve conti

Quantifying the noise sensitivity of the Wasserstein metric for images

arXiv:2510.01015v3 Announce Type: cross Abstract: Wasserstein metrics are increasingly adopted as similarity scores for images. We consider the sensitivity of Wasserstein metrics with respect to pixel

applicationsarxiv-cs-lg

Seeds Before Objectives: Rethinking Evaluation for Low-Resource Garhwali ASR

model-releasesarxiv-cs-cl

arXiv:2608.10670v1 Announce Type: new Abstract: At corpus sizes typical of low-resource dialects, single-run comparisons can yield gains that do not replicate. We show this for Garhwali, an under-reso

TAF-MED: Multi-Turn Safety Refusal Collapse in LLMs Under Declared Self-Treatment Intent

arXiv:2608.10258v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly provide conversational health information that may influence treatment decisions, yet existing benchmarks do

Templated or fully Synthetic? Prompt construction as a confound in measuring LLM political stance beyond writing assistance

arXiv:2608.11008v1 Announce Type: new Abstract: Political stance detection in LLMs has long been dominated by closed-ended, multiple-choice political survey questions---originally designed for humans,

safetyarxiv-cs-cl

Whisper-Aware LLM: Self-Supervised Uncertainty Learning for Robust Whispered Speech Recognition

arXiv:2608.10836v1 Announce Type: cross Abstract: The signal ambiguity of whispered speech drives ASR systems toward two opposing failure modes: failing to capture whispered speech or hallucinatory tr

researcharxiv-cs-ai

Hardware

Beyond Isotropic Assumptions: Continuity-Constrained Segmentation and GPU Morphometry for Nanoscale GBM Analysis

arXiv:2608.07575v1 Announce Type: new Abstract: Confocal microscopy of optically cleared and swelled tissue resolves complex biological structures in 3D, but such acquisitions are highly anisotropic:

hardwarearxiv-cs-cv

GeoAI-based post-segmentation quality validation of building footprints via spatial feature engineering

arXiv:2608.09048v1 Announce Type: new Abstract: Deep learning-based building footprint extraction from high-resolution imagery often produces topologically inconsistent vectors unfit for direct GIS da

applicationsarxiv-cs-cv

Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification

arXiv:2603.19329v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness. Formally verifying that implementations

NeuroPilot: An Agent-Driven Smart Pipeline for Processing, Quality Control, and Managing Neuroimages

arXiv:2608.07541v1 Announce Type: cross Abstract: Transforming raw neuroimage archives into analysis-ready derivatives relies on three brittle stages: data standardization, modality-specific preproces

The Capability Ladder: A Curriculum-Modernization Framework for Workforce Readiness in the AI Era

arXiv:2608.07779v1 Announce Type: new Abstract: Artificial intelligence is changing the task composition of computing work faster than curricula and training typically adapt. This is a curriculum-fram

Unaccountable Delegation, Fading Skills: Mapping the Risks of Workplace AI Agents

arXiv:2608.08601v1 Announce Type: new Abstract: To anticipate socio-technical risks from AI agents, organizations need taxonomies to classify them. However, existing AI risk taxonomies focus on broad

safetyarxiv-cs-ai

UNMASK: Discovering and Causally Verifying Spurious Shortcuts in Text Classifiers

model-releasesarxiv-cs-cl

arXiv:2608.09209v1 Announce Type: new Abstract: Neural language models trained on large crowdsourced corpora frequently exploit spurious surface patterns tied to target labels without true linguistic

Local Ai

Verifiably grounded machine interpretation of lunar geology

arXiv:2608.09276v1 Announce Type: new Abstract: Planetary geology relies on historical, interpretive reasoning to reconstruct past events from diverse observations. Here, we present a step toward an a

local-aiarxiv-cs-cl