Search: “tools”

AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite

arXiv:2510.21652v2 Announce Type: replace Abstract: AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and

23 Apr 2026

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Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations

DGX agent

arXiv:2603.15867v2 Announce Type: replace Abstract: The growing use of Machine Learning (ML) tools comes with critical challenges, such as limited model explainability. We propose a global explainabil

safetyarxiv-cs-lg

23 Apr 2026

Neural Bandit Based Optimal LLM Selection for a Pipeline of Subtasks

arXiv:2508.09958v3 Announce Type: replace Abstract: As large language models (LLMs) become increasingly popular, there is a growing need to predict which out of a set of LLMs will yield a successful a

agentsarxiv-cs-cl

23 Apr 2026

Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph

arXiv:2604.18883v1 Announce Type: cross Abstract: Current AI-assisted programming tools are predominantly linear and chat-based, which deviates from the iterative and branching nature of programming i

researcharxiv-cs-ai

Local Ai

Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents

arXiv:2604.00555v2 Announce Type: replace Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory complianc

local-aiarxiv-cs-ai

Applications

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption

arXiv:2510.18333v2 Announce Type: replace-cross Abstract: Despite progress in watermarking algorithms for large language models (LLMs), real-world deployment remains limited. We argue that this gap st

applicationsarxiv-cs-cl

Rethinking Scale: Deployment Trade-offs of Small Language Models under Agent Paradigms

arXiv:2604.19299v1 Announce Type: cross Abstract: Despite the impressive capabilities of large language models, their substantial computational costs, latency, and privacy risks hinder their widesprea

Applications

RoLegalGEC: Legal Domain Grammatical Error Detection and Correction Dataset for Romanian

arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass

applicationsarxiv-cs-ai

Time Series Augmented Generation for Financial Applications

arXiv:2604.19633v1 Announce Type: new Abstract: Evaluating the reasoning capabilities of Large Language Models (LLMs) for complex, quantitative financial tasks is a critical and unsolved challenge. St

Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks

arXiv:2604.17761v1 Announce Type: cross Abstract: Interpretability tools are increasingly used to analyze failures of Large Language Models (LLMs), yet prior work largely focuses on short prompts or t

researcharxiv-cs-cl

Creating ConLangs to Probe the Metalinguistic Grammatical Knowledge of LLMs

arXiv:2510.07591v3 Announce Type: replace Abstract: We present a system that uses LLMs as a tool in the development of Constructed Languages -- ConLangs, which we call IASC (Interactive Agentic System

Designing Explainable Conversational Agentic Systems for Guarani Speakers

arXiv:2603.05743v3 Announce Type: replace Abstract: Although artificial intelligence (AI) and Human-Computer Interaction (HCI) systems are often presented as universal solutions, their design remains

agentsarxiv-cs-cl

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks

arXiv:2604.17159v1 Announce Type: cross Abstract: We present, to our knowledge, the most comprehensive cross-model evaluation of LLM agents on offensive cybersecurity tasks, benchmarking 10 frontier m

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants

model-releasesarxiv-cs-lg

arXiv:2503.14281v4 Announce Type: replace-cross Abstract: AI coding assistants are widely used for tasks like code generation. These tools now require large and complex contexts, automatically sourced

Bilevel Optimization of Agent Skills via Monte Carlo Tree Search

arXiv:2604.15709v1 Announce Type: new Abstract: Agent exttt{skills} are structured collections of instructions, tools, and supporting resources that help large language model (LLM) agents perform part

Tutorials

Discovering quantum phenomena with Interpretable Machine Learning

arXiv:2604.16015v1 Announce Type: cross Abstract: Interpretable machine learning techniques are becoming essential tools for extracting physical insights from complex quantum data. We build on recent

tutorialsarxiv-cs-lg

The Semi-Executable Stack: Agentic Software Engineering and the Expanding Scope of SE

arXiv:2604.15468v1 Announce Type: cross Abstract: AI-based systems, currently driven largely by LLMs and tool-using agentic harnesses, are increasingly discussed as a possible threat to software engin

Hardware

Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective

arXiv:2511.00739v3 Announce Type: replace Abstract: Agentic AI serving converts monolithic LLM-based inference to autonomous problem-solvers that can plan, call tools, perform reasoning, and adapt on

hardwarearxiv-cs-ai

Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems

arXiv:2604.14228v1 Announce Type: cross Abstract: Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user. This study describes

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

Hierarchical Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

arXiv:2604.14166v1 Announce Type: new Abstract: Mapping Cyber Threat Intelligence (CTI) text to MITRE ATT&CK technique IDs is a critical task for understanding adversary behaviors and automating threa

safetyarxiv-cs-cl

MM-WebAgent: A Hierarchical Multimodal Web Agent for Webpage Generation

arXiv:2604.15309v1 Announce Type: cross Abstract: The rapid progress of Artificial Intelligence Generated Content (AIGC) tools enables images, videos, and visualizations to be created on demand for we

LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification

model-releasesarxiv-cs-lg

arXiv:2603.03959v4 Announce Type: replace-cross Abstract: Code comment classification is a critical task for automated software documentation and analysis. In the context of the NLBSE'26 Tool Competit

16 Apr 2026

Mobius transforms and Shapley values for vector-valued functions on weighted directed acyclic multigraphs

arXiv:2510.05786v3 Announce Type: replace-cross Abstract: Mobius inversion and Shapley values are two mathematical tools for characterizing and decomposing higher-order structure in complex systems. T

researcharxiv-cs-lg

16 Apr 2026

From Imitation to Discrimination: Progressive Curriculum Learning for Robust Web Navigation

arXiv:2604.12666v1 Announce Type: cross Abstract: Text-based web agents offer computational efficiency for autonomous web navigation, yet developing robust agents remains challenging due to the noisy

15 Apr 2026

GCA Framework: A Gulf-Grounded Dataset and Agentic Pipeline for Climate Decision Support

arXiv:2604.12306v1 Announce Type: cross Abstract: Climate decision-making in the Gulf increasingly demands systems that can translate heterogeneous scientific and policy evidence into actionable guida

15 Apr 2026

Applications

A Complete Decomposition of KL Error using Refined Information and Mode Interaction Selection

arXiv:2410.11964v2 Announce Type: replace Abstract: The log-linear model has received a significant amount of theoretical attention in previous decades and remains the fundamental tool used for learni

applicationsarxiv-cs-lg

DeepSketcher: Internalizing Visual Manipulation for Multimodal Reasoning

arXiv:2509.25866v2 Announce Type: replace Abstract: The 'thinking with images' paradigm represents a pivotal shift in the reasoning of Vision Language Models (VLMs), moving from text-dominant chain-of

researcharxiv-cs-cv

FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning

arXiv:2604.10693v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has improved LLM reasoning, but models often generate explanations that appear coherent while containing unfaithful int

LETGAMES: An LLM-Powered Gamified Approach to Cognitive Training for Patients with Cognitive Impairment

arXiv:2604.09566v1 Announce Type: cross Abstract: The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game d

researcharxiv-cs-ai

Machine Learning-Based Detection of MCP Attacks

arXiv:2604.10534v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is a new and emerging technology that extends the functionality of large language models, improving workflows but als

Problem Reductions at Scale: Agentic Integration of Computationally Hard Problems

arXiv:2604.11535v1 Announce Type: new Abstract: Solving an NP-hard optimization problem often requires reformulating it for a specific solver -- quantum hardware, a commercial optimizer, or a domain h

Resilient Write: A Six-Layer Durable Write Surface for LLM Coding Agents

arXiv:2604.10842v1 Announce Type: cross Abstract: LLM-powered coding agents increasingly rely on tool-use protocols such as the Model Context Protocol~(MCP) to read and write files on a developer's wo

Structure-Grounded Knowledge Retrieval via Code Dependencies for Multi-Step Data Reasoning

arXiv:2604.10516v1 Announce Type: new Abstract: Selecting the right knowledge is critical when using large language models (LLMs) to solve domain-specific data analysis tasks. However, most retrieval-

agentsarxiv-cs-cl

The Augmentation Trap: AI Productivity and the Cost of Cognitive Offloading

arXiv:2604.03501v2 Announce Type: replace-cross Abstract: Experimental evidence confirms that AI tools raise worker productivity, but also that sustained use can erode the expertise on which those gai

Agentic Jackal: Live Execution and Semantic Value Grounding for Text-to-JQL

arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com

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

CONDESION-BENCH: Conditional Decision-Making of Large Language Models in Compositional Action Space

arXiv:2604.09029v1 Announce Type: cross Abstract: Large language models have been widely explored as decision-support tools in high-stakes domains due to their contextual understanding and reasoning c

Many-Tier Instruction Hierarchy in LLM Agents

arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level

Scheming in the wild: detecting real-world AI scheming incidents with open-source intelligence

arXiv:2604.09104v1 Announce Type: cross Abstract: Scheming, the covert pursuit of misaligned goals by AI systems, represents a potentially catastrophic risk, yet scheming research suffers from signifi

Beyond Functional Correctness: Design Issues in AI IDE-Generated Large-Scale Projects

arXiv:2604.06373v1 Announce Type: cross Abstract: New generation of AI coding tools, including AI-powered IDEs equipped with agentic capabilities, can generate code within the context of the project.

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

Contrastive Decoding Mitigates Score Range Bias in LLM-as-a-Judge

arXiv:2510.18196v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are commonly used as evaluators in various applications, but the reliability of the outcomes remains a challenge.

Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education

arXiv:2604.07253v1 Announce Type: cross Abstract: In gender-restrictive and surveilled contexts, where access to formal education may be restricted for women, pursuing education involves safety and pr

LLM-based Schema-Guided Extraction and Validation of Missing-Person Intelligence from Heterogeneous Data Sources

arXiv:2604.06571v1 Announce Type: cross Abstract: Missing-person and child-safety investigations rely on heterogeneous case documents, including structured forms, bulletin-style posters, and narrative

SymptomWise: A Deterministic Reasoning Layer for Reliable and Efficient AI Systems

arXiv:2604.06375v1 Announce Type: new Abstract: AI-driven symptom analysis systems face persistent challenges in reliability, interpretability, and hallucination. End-to-end generative approaches ofte

Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning

arXiv:2604.06200v1 Announce Type: cross Abstract: Designing project-based learning (PBL) demands managing highly interdependent components, a task that both traditional linear tools and purely convers

researcharxiv-cs-ai

Towards the Development of an LLM-Based Methodology for Automated Security Profiling in Compliance with Ukrainian Cybersecurity Regulations

arXiv:2604.06274v1 Announce Type: cross Abstract: In recent years, the pace of development of information technology in various areas has increased drastically, forcing cybersecurity specialists to co