Search: “tools”

GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning

arXiv:2510.04567v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) are powerful tools for processing relational data but often struggle to generalize to unseen graphs, giving rise

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Less Effort, Shorter Proofs: Reinforcement Learning for Security Protocol Analysis in Tamarin

DGX agent

arXiv:2605.23643v1 Announce Type: cross Abstract: Tools like Tamarin and ProVerif have achieved notable success in analyzing and verifying complex real-world protocols such as EMV, 5G, and WPA2, even

tutorialsarxiv-cs-lg

25 May 2026

Philosophical Dispositions as Behavioral Constraints for AI-Assisted Code Review: An Empirical Study

arXiv:2605.23108v1 Announce Type: cross Abstract: AI-assisted code review tools typically operate as generic 'expert reviewer' agents, producing homogeneous findings regardless of the analysis type ne

Push Your Agent: Measuring and Enforcing Quantitative Goal Persistence in Long-Horizon LLM Agents

arXiv:2605.23574v1 Announce Type: new Abstract: Long-horizon language agents can make many plausible local tool calls yet fail to persist until a requested count is actually complete. We study this ga

SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval

arXiv:2601.03260v2 Announce Type: replace-cross Abstract: AI agents have seen widespread adoption in information retrieval for scientific research, giving rise to tools such as Deep Research. However,

researcharxiv-cs-cl

When Symptoms Are Not Enough: Evidence-Weighting Patterns in Large Language Model Psychiatric Screening

model-releasesarxiv-cs-cl

arXiv:2605.23148v1 Announce Type: new Abstract: As demand for mental health care outpaces clinician-delivered assessment, scalable screening tools are increasingly needed. Large language models (LLMs)

Hyperparameter Transfer with Mixture-of-Expert Layers

arXiv:2601.20205v3 Announce Type: replace Abstract: Mixture-of-Experts (MoE) layers have emerged as an important tool in scaling up modern neural networks by decoupling total trainable parameters from

Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy

arXiv:2605.21780v1 Announce Type: new Abstract: Randomized smoothing is a powerful tool for certifying robustness to adversarial perturbations, including poisoning attacks via randomized training and

applicationsarxiv-cs-lg

Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring

arXiv:2605.21745v1 Announce Type: new Abstract: Non-contrast computed tomography calcium scoring (CTCS) is widely recognized as an effective tool for cardiovascular risk stratification. This study aim

Truncated Neural Likelihood Estimation for Simulation-Based Inference in State-Space Models

arXiv:2605.21805v1 Announce Type: cross Abstract: State-space models (SSMs) are powerful probabilistic tools for modeling time-varying systems with latent dynamics. Inference in SSMs involves the esti

Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development

arXiv:2605.20456v1 Announce Type: cross Abstract: Agentic AI coding systems can inspect repositories, plan implementation steps, edit files, call tools, run tests, and submit pull requests. These capa

agentsarxiv-cs-ai

Diffusion-guided Generalizable Enhancer for Urban Scene Reconstruction

arXiv:2605.22420v1 Announce Type: new Abstract: Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural re

agentsarxiv-cs-cv

EvoIR-Agent: Self-Evolving Image Restoration Agentic System via Experience-Driven Learning

arXiv:2605.22208v1 Announce Type: new Abstract: Multimodal Large Language Model (MLLM)-driven image restoration agent demonstrates effectiveness in degradation coupling scenarios by flexibly selecting

agentsarxiv-cs-cv

FlyRoute: Self-Evolving Agent Profiling via Data Flywheel for Adaptive Task Routing

arXiv:2605.22057v1 Announce Type: new Abstract: Enterprise routers assign queries to expert agents, yet deployed profiles stay static while agents evolve (prompts, tools, models), and developers rarel

Modeling Pathology-Like Behavioral Patterns in Language Models Through Behavioral Fine-Tuning

arXiv:2605.22356v1 Announce Type: new Abstract: Large language models are increasingly used as computational tools for modeling human-like behavior. We introduce a behavioral induction framework that

Multi-Stage Training for Abusive Comment Detection in Indic Languages

arXiv:2605.22380v1 Announce Type: new Abstract: In recent years social media has become an increasingly popular tool for communication. People use it to share their ideas, exchange information, and di

researcharxiv-cs-cl

'Would You Want an AI Tutor?' Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom

arXiv:2503.02885v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following ea

ACL-Verbatim: hallucination-free question answering for research

model-releasesarxiv-cs-cl

arXiv:2605.21102v1 Announce Type: new Abstract: Academic researchers need efficient and reliable methods for collecting high-quality information from trusted sources, but modern tools for AI-assisted

FAIR-Pruner: A Flexible Framework for Automatic Layer-Wise Pruning via Tolerance of Difference

arXiv:2508.02291v3 Announce Type: replace Abstract: Structured pruning is a standard tool for compressing deep neural networks, but its practical performance depends on how sparsity is allocated acros

Federated LoRA Fine-Tuning for LLMs via Collaborative Alignment

arXiv:2605.21217v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has emerged as a powerful tool for parameter-efficient fine-tuning of large language models (LLMs). This paper studies LoRA

HAPS: Rethinking Image Similarity for Virtual Staining

arXiv:2605.20362v1 Announce Type: new Abstract: Virtual staining of histopathology images (e.g., H&E-IHC) is an emerging tool in digital pathology, enabling faster and cheaper workflows by synthesizin

researcharxiv-cs-cv

Learning fMRI activations dictionaries across individual geometries via optimal transport

arXiv:2605.20883v1 Announce Type: new Abstract: Dictionary learning is a powerful tool for creating interpretable representations. When applied to functional magnetic resonance imaging (fMRI) data, th

Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs

arXiv:2605.20315v1 Announce Type: new Abstract: LLM agents have recently emerged as a powerful paradigm for solving complex tasks through planning, tool use, memory retrieval, and multi-step interacti

agentsarxiv-cs-cl

Temporal Counterfactual Explanations of Behaviour Tree Decisions

arXiv:2509.07674v2 Announce Type: replace Abstract: Explainability, in particular, the ability for robots to explain why they have made a decision or behaved in a certain way, is a critical tool in he

researcharxiv-cs-ro

Automatically Improving Simulation Physics for Articulated Objects

arXiv:2605.19136v1 Announce Type: new Abstract: Simulation is a central tool for scalable robot learning, but its effectiveness depends on the quality of object assets. While modern 3D datasets provid

safetyarxiv-cs-ro

CAIT: A Syntactic Parsing Toolkit for Child-Adult InTeractions

arXiv:2605.19718v1 Announce Type: new Abstract: CHILDES is a paramount resource for language acquisition studies -- yet computational tools for analyzing its syntactic structure remain limited. Levera

applicationsarxiv-cs-cl

Convergence rates for gradient descent in the training of overparameterized artificial neural networks with piecewise affine activation

arXiv:2102.11840v2 Announce Type: replace Abstract: In recent years, artificial neural networks have developed into a powerful tool for addressing a multitude of problems for which classical solution

Tutorials

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies

arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application

tutorialsarxiv-cs-lg

ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation

arXiv:2602.04279v2 Announce Type: replace Abstract: Electrocardiography (ECG) serves as an indispensable diagnostic tool in clinical practice, yet existing multimodal large language models (MLLMs) rem

researcharxiv-cs-cl

MedFM-Robust: Benchmarking Robustness of Medical Foundation Models

model-releasesarxiv-cs-cv

arXiv:2605.19027v1 Announce Type: new Abstract: Medical foundation models (MedFMs) have emerged as transformative tools in healthcare, demonstrating capabilities across diverse clinical applications.

optimize_anything: A Universal API for Optimizing any Text Parameter

arXiv:2605.19633v1 Announce Type: cross Abstract: Can a single LLM-based optimization system match specialized tools across fundamentally different domains? We show that when optimization problems are

Optimizing Computational-Statistical Runtime for Wasserstein Distance Estimation

arXiv:2605.20122v1 Announce Type: cross Abstract: Squared Wasserstein distance is a frequently used tool to measure discrepancy between probability distributions. This distance is typically computed b

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence

arXiv:2605.18893v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are powerful tools for learning from graph-structured data, but their scalability is increasingly strained by the size of r

applicationsarxiv-cs-lg

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents

arXiv:2605.18882v1 Announce Type: cross Abstract: LLM agents exhibit a consistent tendency to over-call, invoking tools even in situations where none is needed. On the When2Call benchmark, six models

Walsh-Hadamard Neural Operators for Solving PDEs with Discontinuous Coefficients

arXiv:2511.07347v2 Announce Type: replace-cross Abstract: Neural operators have emerged as powerful tools for learning solution operators of partial differential equations (PDEs). However, standard sp

1GC-7RC: One Graphic Card -- Seven Research Challenges! How Good Are AI Agents at Doing Your Job?

arXiv:2605.17046v1 Announce Type: cross Abstract: Autonomous AI coding agents are becoming a core tool for ML practitioners in industry and research alike. Despite this growing adoption, no standardiz

An Analytical Multiple Criteria Framework for Temporal and Dynamic Business-to-Business Customer Segmentation in Manufacturing

arXiv:2605.17151v1 Announce Type: new Abstract: In sales and marketing, customer segmentation is an important tool for formulating strategies for customer treatment and supply chain management. Most s

applicationsarxiv-cs-lg

Are Sparse Autoencoder Benchmarks Reliable?

arXiv:2605.18229v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are a core interpretability tool for large language models, and progress on SAE architectures depends on benchmarks that re

Beyond MMSE: Enhancing PnP Restoration with ProxiMAP

arXiv:2605.16396v1 Announce Type: new Abstract: Plug-and-Play (PnP) methods have become standard tools for solving imaging inverse problems by replacing the intractable maximum a posteriori (MAP) deno

researcharxiv-cs-cv

CAM-VFD: Cross-Attention Multimodal Video Forgery Detection

arXiv:2605.17133v1 Announce Type: cross Abstract: The rapid advancement of Deepfake technologies and video manipulation tools poses a critical challenge to multimedia forensics, judicial evidence inte

Compress the Context, Keep the Commitments: A Formal Framework for Verifiable LLM Context Compression

arXiv:2605.17304v1 Announce Type: cross Abstract: LLM context is not just tokens; it is a set of commitments. Long-running conversations accumulate goals, constraints, decisions, preferences, tool res

DISA: Offline Importance Sampling for Distribution-Matching LLM-RL

arXiv:2605.17295v1 Announce Type: cross Abstract: Modern reasoning agents are increasingly evaluated on their ability to generate multiple valid solution paths, plans, or tool-use traces for a given i

Emulating the Forced Response of Climate Models with Flow Matching

arXiv:2605.16929v1 Announce Type: new Abstract: Global climate models are essential tools to simulate past and potential future pathways of climate change, as well as associated climate impacts. Share

Evidential Information Fusion on Possibilistic Structure

arXiv:2605.17038v1 Announce Type: new Abstract: Dempster's rule is a fundamental tool for combining belief functions from distinct and reliable sources. However, its intersection-based semantics impos

From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

safetyarxiv-cs-ai

GraphMind: From Operational Traces to Self-Evolving Workflow Automation

arXiv:2605.17617v1 Announce Type: new Abstract: Complex operational workflows coordinating personnel, tools, and information are central to enterprise operations, yet end-to-end automation remains cha

agentsarxiv-cs-ai

Interactive Evaluation Requires a Design Science

arXiv:2605.17829v1 Announce Type: new Abstract: AI evaluation is undergoing a structural change. Large language models (LLMs) are increasingly deployed as systems that act over time through tools, env

agentsarxiv-cs-ai

LSDTs: LLM-Augmented Semantic Digital Twins for Adaptive Knowledge-Intensive Infrastructure Planning

arXiv:2508.06799v3 Announce Type: replace-cross Abstract: Digital Twins (DTs) offer powerful tools for managing complex infrastructure systems, but their effectiveness is often limited by challenges i

applicationsarxiv-cs-ai