Search: “automated”

Converge Then Diversify: Decoupling Convergence and Diversity in Multi-Objective Bayesian Optimisation

arXiv:2609.13396v1 Announce Type: new Abstract: Multi-objective Bayesian optimisation (MOBO) is a sample-efficient approach for optimising expensive black-box functions with multiple objectives. In MO

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Do Tabular Foundation Models Still Need Feature Engineering?

DGX agent

arXiv:2609.13202v1 Announce Type: new Abstract: Feature engineering has long been a cornerstone of tabular machine learning. Tabular foundation models (TFMs) are pretrained on a wide range of tabular

model-releasesarxiv-cs-lg

15 Sept 2026

Domain-specific Pretraining Profile and Transformer Performance: Evidence from Modeling Digital Pragmatics in Arabic-English Code-switching

arXiv:2609.14571v1 Announce Type: new Abstract: This study highlights the role of domain-specific pretraining profile (DSPP) in Transformer performance for modeling digital pragmatics in Arabic-Englis

ECAS: An Edge-Controlled Agentic System for Validation-Gated Scientific Application Execution

arXiv:2609.14211v1 Announce Type: cross Abstract: Scientific applications increasingly rely on high-performance computing (HPC), yet translating a scientist's high-level goal into a correct target-sca

safetyarxiv-cs-ai

HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses

arXiv:2609.15938v1 Announce Type: new Abstract: Scientific agents contribute to hypothesis discovery by synthesizing evidence, assessing proposals, and developing new explanations. Recent systems comb

agentsarxiv-cs-cl

Tutorials

Multi4D: an end-to-end neural network for structural determination at complex material interfaces

arXiv:2609.14348v1 Announce Type: cross Abstract: Heterogeneous interfaces dictate the performance and degradation of functional materials, making it essential to link local structural variations with

tutorialsarxiv-cs-cv

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

arXiv:2609.13463v1 Announce Type: new Abstract: The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reli

SAILOR: Solver-Assisted Interactive LLM-based Optimization Recovery

arXiv:2609.13945v1 Announce Type: new Abstract: Natural-language descriptions of optimization problems may be incomplete or vague about numerical information that a solver requires, including costs, c

Tone on a Budget: A Reference-Free Metric for Lexical Tone in Massively Multilingual Text-to-Speech

arXiv:2609.14817v1 Announce Type: new Abstract: In Yoruba, pitch alone separates oko (husband, Mid), okd{o (vehicle, Low), and okd{o (hoe, High) -- the diacritics ARE the tone marks. Yet character err

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

arXiv:2609.15964v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but t

When Compliance Data Masquerades as Evaluation: Measurement Validity for Deployed AI Systems

arXiv:2609.13642v1 Announce Type: new Abstract: We argue that a recurring failure in the evaluation of deployed AI systems occurs when data collected for operational monitoring or regulatory complianc

safetyarxiv-cs-lg

Hardware

AMDKernelVault: Large-Scale Datasets and Agentic Training for AMD GPU Kernel Optimization

arXiv:2609.12471v1 Announce Type: new Abstract: We introduce AMDKernelVault, an open HIP and Triton kernel corpus and training framework for recent AMD CDNA GPUs. Existing LLM-based kernel agents are

hardwarearxiv-cs-cl

GRACE-DS: a Guarded Reward-guided Agent Correction Environment in Data Science

arXiv:2606.16000v3 Announce Type: replace Abstract: We introduce GRACE-DS, a Guarded Reward-guided Agent Correction Environment in Data Science for pre-deployment evaluation of LLM-powered AutoML agen

safetyarxiv-cs-cl

Online Video Agent Harness for Long Video Understanding

arXiv:2609.12818v1 Announce Type: new Abstract: Long video understanding often behaves like a visual needle-in-a-haystack problem: query-relevant evidence is sparsely distributed across long temporal

agentsarxiv-cs-cv

PRISMA-LLM: An Empirical Reporting Framework for AI-Assisted Systematic Reviews

arXiv:2609.11559v1 Announce Type: cross Abstract: Large language models (LLMs) and AI-enabled software increasingly participate in systematic-review decisions, yet the information needed to audit thes

SV-Cine: Diagnosis-Conditioned Segmentation of Single Ventricle Physiology via Generative Data Augmentation

arXiv:2609.12997v1 Announce Type: new Abstract: Single Ventricle Physiology (SVP) is a rare subtype of congenital heart disease characterized by the presence of a single functional cardiac ventricle w

researcharxiv-cs-cv

An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc

arXiv:2603.15976v2 Announce Type: replace Abstract: While LLMs have accelerated scientific code generation, comprehensively evaluating generated code remains challenging. Many benchmarks emphasize fun

12 Sept 2026

Generating a Consistent Enterprise: Synthesis and Reference-Free Evaluation of Multi-System Business Data

arXiv:2609.11286v1 Announce Type: new Abstract: Synthetic relational data is normally produced by a model trained on a real dataset, and its quality is measured as the distance to that dataset. This p

12 Sept 2026

How AI Coders Discuss, Disagree, and Reach Consensus: Challenges and Opportunities for LLM-Based Qualitative Coding

arXiv:2609.11109v1 Announce Type: cross Abstract: The utility of AI in multi-coder qualitative coding has been widely discussed, yet little empirical evidence exists to delineate the contexts in which

12 Sept 2026

A Comparative Evaluation of Pre-trained Convolutional Neural Networks for Melanoma Detection

arXiv:2609.11550v1 Announce Type: new Abstract: Early diagnosis of melanoma is critical for improving patient survival rates. However, accurately distinguishing melanoma from other skin lesions remain

researcharxiv-cs-cv

An Experimental Evaluation of Multimodal Prompt Injection Attacks on Agentic AI Frameworks

arXiv:2609.09404v1 Announce Type: cross Abstract: Agentic AI frameworks let a language model plan, keep memory, and call tools that reach real files, mail, and services. Most of these agents also read

Assessing the Reusability of Public Speech Resources for Low-Resource Languages: A Central Kurdish Case Study

arXiv:2609.11246v1 Announce Type: new Abstract: Kurdish is spoken by millions of people, but little technology can read it aloud. A recent study released three Kurdish voices, 35 hours of recorded spe

Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization

arXiv:2609.11141v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate structured outputs, but their reliability remains unclear when those outputs must satisfy

Cognitive Digital Twins: Ethical Risks and Governance for AI Systems That Model the Mind

arXiv:2606.23094v2 Announce Type: replace-cross Abstract: As AI systems become increasingly persistent and personalized, they make possible a class of technologies that we call cognitive digital twins

agentsarxiv-cs-cl

Complex-Text Robustness Evaluation and Failure Diagnosis for Low-Resource Multilingual Text-to-Speech

arXiv:2609.11545v1 Announce Type: new Abstract: Low-resource multilingual text-to-speech (TTS) systems have expanded language coverage, but their robustness under complex text inputs remains insuffici

Diversity of EML-type operators

arXiv:2609.11210v1 Announce Type: cross Abstract: The discovery of the EML operator, sufficient to evaluate the standard explicit purely transcendental elementary functions, has led to considerable in

researcharxiv-cs-lg

Evidence for Limited Metacognition in LLMs

arXiv:2509.21545v3 Announce Type: replace Abstract: The possibility of LLM self-awareness and even sentience is gaining increasing public attention and has major safety and policy implications, but th

safetyarxiv-cs-lg

ExpTest: Loss-Curve Hypothesis Testing for Autonomous Learning-Rate Selection in Deep Neural Networks

arXiv:2411.16975v2 Announce Type: replace Abstract: Hyperparameter tuning remains a significant challenge in the training of deep neural networks (DNNs), requiring manual search or time-intensive grid

agentsarxiv-cs-lg

Learning Intrusion Response Strategies for OT Systems

arXiv:2609.10298v1 Announce Type: cross Abstract: Cyberattacks against Operational Technology (OT) systems, which monitor and control industrial processes, pose an increasing threat to essential socie

Numbat: Building and Verifying a Self-Contained Machine-Learning Stack

model-releasesarxiv-cs-lg

arXiv:2609.10632v1 Announce Type: cross Abstract: Machine-learning systems are built almost exclusively on a few large Python-orchestrated frameworks, and they inherit those stacks' engineering costs:

ProMediConv: Benchmarking Proactive Conversational Agents in Legal Dispute Mediation

arXiv:2609.11101v1 Announce Type: new Abstract: Dispute mediation is essential for maintaining social harmony and resilience, yet developing skilled mediators is costly and time-consuming. Existing LL

RobustSGPO: Search-Space Control for Agent Harness Evolution

arXiv:2609.09646v1 Announce Type: new Abstract: Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edi

Adversarial Training for Tabular Credit Scoring: A Multi-Attack Robustness Evaluation in P2P Lending

model-releasesarxiv-cs-lg

arXiv:2609.09945v1 Announce Type: new Abstract: Machine learning-based credit scoring is increasingly central to Peer-to-Peer (P2P) lending, yet its resilience to adversarial manipulation, where appli

An Efficient and Effective Agentic Group Shilling Attack on Recommender Systems

arXiv:2609.09551v1 Announce Type: cross Abstract: Recommender systems have become core infrastructure for modern online platforms, personalizing content at scale and strongly influencing what users se

agentsarxiv-cs-cl

Artificial Intelligence-Assisted Digital Inventory of Cultural Heritage & Traditional Knowledge: Case for Indonesian Open Digital Library of Culture

arXiv:2609.08105v1 Announce Type: new Abstract: The Indonesian Digital Library of Culture (Perpustakaan Digital Budaya Indonesia, PDBI; budaya-indonesia.org) is a participatory platform that has colle

AutoKD: Autonomous Knowledge Discovery

arXiv:2609.06366v1 Announce Type: new Abstract: Scientific discovery in data-rich domains is currently constrained by human bandwidth: the growth in the volume and complexity of real-world data far ou

BTBR: A Bayesian-Theory-Driven Probabilistic-Fuzzy Framework for Implicit Bias Removal in Large Language Models

arXiv:2408.10608v2 Announce Type: replace Abstract: Large language models (LLMs) may encode biased associations from heterogeneous training corpora that are not immediately visible under ordinary prom

safetyarxiv-cs-cl

Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails

arXiv:2609.09134v1 Announce Type: new Abstract: Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agentic

Cyber-Financial Contagion: Modeling the Propagation of an AI Vendor Compromise Through the Banking System

arXiv:2609.10350v1 Announce Type: cross Abstract: The banking system now depends on a small set of shared artificial intelligence vendors for fraud screening, credit decisioning, anti-money-laundering

researcharxiv-cs-lg

Evidence-Grounded Retrieval for Investigation Hunt Lead Generation from CTI Reports

arXiv:2609.08790v1 Announce Type: cross Abstract: Threat hunting increasingly depends on converting unstructured knowledge (e.g., Cyber Threat Intelligence reports) into actionable hunt leads: concise

Experimental Analysis of Productive Interaction Strategy with ChatGPT: User Study on Function and Project-level Code Generation Tasks

arXiv:2508.04125v2 Announce Type: replace-cross Abstract: The application of Large Language Models (LLMs) is growing in the productive completion of Software Engineering tasks. Yet, studies investigat

Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Search

arXiv:2609.10225v1 Announce Type: new Abstract: Feature transformation improves predictive performance on tabular data by constructing informative abstractions from raw features. Recent generative app

safetyarxiv-cs-lg

Improving Proficiency and Efficiency of Android GUI Agents via Self-Generating Tool Actions

arXiv:2609.06792v1 Announce Type: new Abstract: Android agents using a hybrid action space that combines GUI actions and tool actions (e.g., accessing application data via APIs) remain largely underex

In Medical Claims Data, Enhancing Predictive Performance for Major Adverse Cardiovascular Events Using Cross Attention

model-releasesarxiv-cs-lg

arXiv:2609.09824v1 Announce Type: new Abstract: Medical claims data comprise the financial details, including the expenses and billing information, as well as the clinical information, such as the dia

ProcArena: A Multi-Scenario Benchmark for LLMs on Direct and Interactive PL/SQL Development from Natural Language

arXiv:2609.06527v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for translating natural-language (NL) requirements into PL/SQL programs, attracting increasin

SCIRIGOR:Evaluating Open-Ended Scientific Analysis Beyond Final Scores

arXiv:2609.06192v1 Announce Type: new Abstract: Scientific coding agents produce interdependent code, results, figures, and claims, yet evaluating final outputs alone does not establish whether their

StochBench: A Domain-Specific Benchmark for Stochastic Processes in Lean

arXiv:2609.09264v1 Announce Type: new Abstract: Leading benchmarks for formal theorem proving with large language models are small collections drawn from competition math, such as the IMO and Putnam,

SWE-Bench Pro Verified: A Reliable Benchmark for Software Engineering Agents

arXiv:2609.08149v1 Announce Type: new Abstract: SWE-Bench Pro has emerged as a standard benchmark for evaluating software engineering agents on challenging repository-level tasks. However, our analysi