Search: “tools”

'Chi nas dal soch el sent de legn' -- Auditing Text Corpora for Lombard

arXiv:2606.06349v1 Announce Type: new Abstract: Several of the world's languages are still under-resourced in terms of Natural Language Processing (NLP) tools. This is mostly due to the lack of high-q

safetyarxiv-cs-cl

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Faithful, Enriched, and Precise: Benchmarking Natural-Science Illustration Generation by T2I models

DGX agent

arXiv:2606.05949v1 Announce Type: new Abstract: Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts a

model-releasesarxiv-cs-cv

5 Jun 2026

Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration

arXiv:2606.06388v1 Announce Type: cross Abstract: Recent advances in LLM agents have enabled complex cognitive capabilities, such as multi-step reasoning, planning, and tool use, that increasingly pos

Interpreting Style Representations via Style-Eliciting Prompts

arXiv:2606.05716v1 Announce Type: new Abstract: Style representation learning is a powerful tool for authorship analysis and modeling writing style, yet the latent nature of learned representations ma

researcharxiv-cs-cl

Retrospective Harness Optimization: Improving LLM Agents via Self-Preference over Trajectory Rollouts

arXiv:2606.05922v1 Announce Type: cross Abstract: AI agents rely on a harness of skills, tools, and workflows to solve complex problems. Continually improving this harness is essential for adapting to

agentsarxiv-cs-cl

An Open-Source Two-Stage Computer Vision Pipeline for Fine-Grained Vehicle Classification using Vision Transformers

model-releasesarxiv-cs-cv

arXiv:2606.05149v1 Announce Type: new Abstract: Vehicle body type is a significant determinant of cyclist injury severity in overtaking crashes, yet automated tools for classifying vehicles into injur

Tutorials

Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

arXiv:2606.04924v1 Announce Type: new Abstract: The widespread use of Large Language Models (LLMs) as writing tools challenges the validity of crowdsourced data, as crowdworkers may outsource tasks to

tutorialsarxiv-cs-cl

Counterfactual Explanations for Deep Two-Sample Testing

arXiv:2606.04009v1 Announce Type: cross Abstract: Two-sample testing is a fundamental tool for detecting distributional differences across scientific domains, but classical tests (including kernel-bas

Efficient Adversarial Attacks on High-dimensional Offline Bandits

arXiv:2602.01658v2 Announce Type: replace-cross Abstract: Bandit algorithms have recently emerged as a powerful tool for evaluating machine learning models, including generative image models and large

Evaluating Autoformalization Robustness via Semantically Similar Paraphrasing

arXiv:2511.12784v3 Announce Type: replace Abstract: Large Language Models (LLMs) have recently emerged as powerful tools for autoformalization. Despite their impressive performance, these models can s

researcharxiv-cs-cl

From Prompt to Process: a Process Taxonomy and Comparative Assessment of Frameworks Supporting AI Software Development Agents

arXiv:2606.04967v1 Announce Type: cross Abstract: AI tools for programming are no longer just autocomplete or chat assistants: they organize themselves as development frameworks, with process, roles,

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

arXiv:2606.05015v1 Announce Type: new Abstract: World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet h

safetyarxiv-cs-ro

IMPose: Interactive Multi-person Pose Estimation with Dynamic Correction Propagation

arXiv:2606.04480v1 Announce Type: new Abstract: High-quality dynamic human pose annotation equips AI with precise motion kinematics to enable human behavior mastery, yet remains labor-intensive and ti

researcharxiv-cs-cv

Long Live Fine-Tuning: Task-Specific Transformers Outperform Zero-Shot LLMs for Misinformation Response Classification on Reddit

arXiv:2606.04274v1 Announce Type: new Abstract: As large language models (LLMs) become default tools for online information verification, an implicit assumption follows them: that scale and general ca

Local Ai

R-APS: Compositional Reasoning and In-Context Meta-Learning for Constrained Design via Reflective Adversarial Pareto Search

arXiv:2606.04823v1 Announce Type: new Abstract: Large language models (LLMs) are fluent on open-ended tasks, yet in agentic settings, where a system must plan, use tools, and act over extended horizon

local-aiarxiv-cs-ai

Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection

arXiv:2606.04453v1 Announce Type: new Abstract: Radiomics enables extraction of quantitative imaging biomarkers from medical images and has become an important tool for computer-aided cancer diagnosis

researcharxiv-cs-cv

SharpNet: Enhancing MLPs to Represent Functions with Controlled Non-differentiability

arXiv:2601.19683v2 Announce Type: replace Abstract: Multi-layer perceptrons (MLPs) are a standard tool for learning and function approximation, but they inherently produce globally smooth outputs. Con

researcharxiv-cs-cv

SpliceBind: Isoform-Aware Prediction of Binding Pocket Druggability

arXiv:2606.04020v1 Announce Type: cross Abstract: Splice-mediated drug resistance occurs in up to 40% of patients on targeted kinase inhibitors, yet state-of-the-art druggability tools operate on sing

TIDE: Proactive Multi-Problem Discovery via Template-Guided Iteration

arXiv:2606.04743v1 Announce Type: cross Abstract: Agents are widely deployed as assistants over documents, tools, and code. However, they typically act only on explicit user requests, which surface on

Applications

A Robust Optimization Approach to Sparse Principal Component Analysis

arXiv:2606.03553v1 Announce Type: cross Abstract: While principal component analysis (PCA) is a fundamental tool for dimensionality reduction, its dense representations make it ill-suited for high-dim

applicationsarxiv-cs-lg

Aligning Data-Driven Predictors with Allocation: A Decision-Focused Approach to Survival Analysis

arXiv:2606.02671v1 Announce Type: cross Abstract: Machine learning predictors have become essential tools for guiding automated decision making. However, a major misalignment persists: predictive mode

Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement

arXiv:2605.11954v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables t

Applications

Calibrating Urban Traffic Simulation from Sparse Road Observations via Genetic Optimization

arXiv:2606.03823v1 Announce Type: new Abstract: Urban traffic simulation is a critical tool for infrastructure planning, including the placement of electric vehicle charging stations. However, realist

applicationsarxiv-cs-ai

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning

arXiv:2606.02998v1 Announce Type: new Abstract: Automated cough analysis offers a path to low-cost respiratory screening, but most existing work stops at binary COVID-19 detection. A practical tool ne

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models

arXiv:2506.03087v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have become essential tools for analyzing graph-structured data in domains such as drug discovery and financial a

Generating the Modal Worker: A Cross-Model Audit of Race and Gender in LLM-Generated Personas Across 41 Occupations

arXiv:2510.21011v3 Announce Type: replace-cross Abstract: As generative AI tools are increasingly used to portray people in professional roles, understanding their racial and gender representational b

Large Byte Model: Teaching Language Models About Compiled Code

arXiv:2606.02834v1 Announce Type: cross Abstract: Malware analysis starts with the raw bytes of an executable program, and tools to 'lift' these to higher-level representations, such as assembly, are

Limit Analysis of Graph Neural Networks with Wireless Conflict Graphs

arXiv:2606.03794v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as a powerful tool for wireless resource allocation that leverages the underlying graph structure of communica

LLM-Assisted Reranking to Operationalize Nuanced Objectives in Recommender Systems

arXiv:2606.02883v1 Announce Type: cross Abstract: Recommender systems have grown from content-organization tools into sophisticated systems that shape daily behavior. By controlling what we see, they

Suboptimality bounds for trace-bounded SDPs enable a faster and scalable low-rank SDP solver SDPLR+

arXiv:2406.10407v3 Announce Type: replace-cross Abstract: Semidefinite programs (SDPs) and their solvers are powerful tools with many applications in machine learning and data science. Designing scala

The Reliability Gap in Benchmark Auditing: Distribution Shift and Scale as Failure Modes of Contamination Detection

arXiv:2606.03305v1 Announce Type: new Abstract: Benchmark contamination, where evaluation examples appear in a model's training data, threatens the validity of LLM assessment. Statistical tools for de

Local Ai

Toward a Modular Architecture for Embedded AI Agent Systems at the Edge

arXiv:2606.02862v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has enabled agentic AI capable of complex reasoning and tool use; however, deploying such autonomy in pervasive

local-aiarxiv-cs-ai

Tutorials

What Do Students Learn? A Feature-Level Analysis of Dark Knowledge

arXiv:2606.03052v1 Announce Type: new Abstract: Knowledge Distillation (KD) is a powerful tool for model compression, yet the precise mechanisms by which student models acquire feature representations

tutorialsarxiv-cs-lg

Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams

arXiv:2606.01770v1 Announce Type: cross Abstract: Auto-harness systems such as A-Evolve, GEPA, and Meta-Harness improve LLM agents by optimizing prompts, skills, tools, memories, and supporting infras

Agentic-J: An AI Agent for Biological Microscopy Image Analysis

arXiv:2606.02080v1 Announce Type: cross Abstract: Biological image analysis increasingly demands integration across heterogeneous tools, programming environments, and domain knowledge that few researc

BranPO: Scalable Contrastive Branch Sampling for Long-Horizon Agentic Reinforcement Learning

arXiv:2602.03719v2 Announce Type: replace Abstract: Agentic reinforcement learning enables large language models to perform multi-turn planning and tool use, but long-horizon training remains challeng

safetyarxiv-cs-cl

BraveGuard: From Open-World Threats to Safer Computer-Use Agents

arXiv:2606.01166v1 Announce Type: cross Abstract: Computer-use agents extend language models from text generation to sustained interaction with files, terminals, browsers, and external tools. This shi

Can AI Review Improve Paper Drafting? An Empirical Study on 20 Computer Architecture Submissions

arXiv:2606.01013v1 Announce Type: new Abstract: Research is advancing faster than ever with artificial intelligence (AI); and so are the corresponding research papers. The exploding volume of AI-gener

Characterization of Multi-Model Agentic AI Systems on General Tasks via Trace-Driven Simulation

arXiv:2606.01725v1 Announce Type: new Abstract: Agentic AI completes tasks through iterative planning, tool use, and reasoning based on observed outcomes. Despite its popularity, its system-level beha

ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree

arXiv:2606.01494v1 Announce Type: cross Abstract: Agent skills extend AI agents with reusable instructions, tools, scripts, references, and workflows, establishing a security boundary distinct from bo

Deliberative Curation: A Protocol for Multi-Agent Knowledge Bases

arXiv:2606.00007v1 Announce Type: new Abstract: As AI agents transition from isolated tools to collaborative participants in shared knowledge ecosystems, governing collective knowledge curation become

I-WebGenBench : Evaluating Interactivity in LLM-Generated Scientific Web Applications

arXiv:2606.00750v1 Announce Type: new Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, existing

Inner Product Aware Quantization: Provably Fast, Accurate, and Adaptive Algorithms

arXiv:2606.00289v1 Announce Type: new Abstract: Quantization is a fundamental tool used to compress datasets, neural network weights, and memory usage in a range of computational tasks. Many downstrea

LLM4Cov: Execution-Aware Agentic Learning for High-coverage Testbench Generation

arXiv:2602.16953v3 Announce Type: replace Abstract: Execution-aware LLM agents offer a promising paradigm for learning from tool feedback, but such feedback can be expensive and slow to obtain, making

Masking Stale Observations Helps Search Agents -- Until It Doesn't: A Regime Map and Its Mechanism

arXiv:2606.00408v1 Announce Type: cross Abstract: Long-horizon search agents accumulate large amounts of retrieved content across many tool calls, making context-budget efficiency increasingly importa

MINTS: Minimalist Thompson Sampling

arXiv:2606.01655v1 Announce Type: cross Abstract: The Bayesian paradigm offers principled tools for sequential decision-making under uncertainty, but its reliance on a probabilistic model for all para

NormEval: A Unified Multi-Metric Framework for Evaluating Semantic Fidelity in Text Normalization

arXiv:2511.20409v2 Announce Type: replace Abstract: Text normalization methods such as stemming and lemmatization are fundamental components of NLP pipelines. As new normalization tools are developed

safetyarxiv-cs-cl

PaperVoyager : Building Interactive Web with Visual Language Models

arXiv:2603.22999v3 Announce Type: replace Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, exist