Search: “tools”

Neural Barriers: An Online Certifiable Learning-enhanced Adaptive High Order Safety Critical Control

arXiv:2610.05542v1 Announce Type: new Abstract: Control barrier functions are an effective model-based tool to formally certify the safety of a system. However, transferring their theoretical guarante

safetyarxiv-cs-ro

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REFLEX: Reflective Evolution from LLM Experience

DGX agent

arXiv:2606.16496v2 Announce Type: replace-cross Abstract: Large multimodal language models (MLLMs) have emerged as powerful tools for guiding evolutionary search toward interpretable programmatic poli

researcharxiv-cs-lg

6 Oct 2026

ScopeSAE: Model-Scope Feature Discovery with Interpretable Layer Selection

arXiv:2610.04905v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are a central tool in mechanistic interpretability. However, existing SAEs are primarily trained per layer. The modeling subs

Spatial Supervision Without Attribution Optimization: Improving Post-Hoc Class Activation Maps via Box-Guided Evidence Routing

arXiv:2610.05891v1 Announce Type: new Abstract: Post-hoc class activation maps (CAMs) are a standard tool for inspecting the evidence behind an image classifier's predictions, yet nothing in ordinary

researcharxiv-cs-cv

STC-MPM: Coupled Deformation, Progressive Damage, and Cut Formation in Soft-Tissue Cutting

arXiv:2610.06198v1 Announce Type: new Abstract: Cutting is a recurring operation in robotic au tomation, from food preparation to surgical tissue resection. For highly compliant targets, blade motion

safetyarxiv-cs-ro

Local Ai

TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being Feedback

arXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf

local-aiarxiv-cs-lg

Tutorials

Variance-Optimal Control Variates for Learning with Black-box Feedback

arXiv:2610.04766v1 Announce Type: new Abstract: Modern models increasingly learn through black-box oracles such as humans, optimization solvers, and external tools that provide feedback without exposi

tutorialsarxiv-cs-lg

Beyond Single Videos: Benchmarking and Active Evidence Seeking for E-Commerce Cross-Video Reasoning

arXiv:2610.03099v1 Announce Type: cross Abstract: E-commerce videos are information-dense and frequently compared by consumers evaluating products and merchants assessing marketing strategies. However

Applications

Certified Mechanistic Edits: Behavioral Guarantees for Skill Removal and Preservation

arXiv:2610.03502v1 Announce Type: cross Abstract: Mechanistic edits (ablations, weight edits, activation steering) are the standard tools for unlearning a harmful capability from a neural network whil

applicationsarxiv-cs-ai

D2K-Bench: Can LLM Agents Turn Expert Designs into Efficient GPU Kernels?

arXiv:2610.03226v1 Announce Type: cross Abstract: GPU kernels generated by large language model (LLM) agents can remain less efficient than expert implementations, but runtime alone does not reveal ho

EvoRiskBench: An Evolving Benchmark for Runtime Security Risks in Workspace Agents

arXiv:2610.03153v1 Announce Type: cross Abstract: Workspace agents combine large language models with execution harnesses to perform stateful, multi-step tasks that access or modify external resources

From Migration to Calibration: Preserving Agent Capabilities across Models, Jurisdictions, and Scale

arXiv:2609.35149v2 Announce Type: replace Abstract: Deploying, migrating, or scaling an agent can change its model, harness, infrastructure, application, and intended users. We formulate agent calibra

Generalizable single-cell perturbation response prediction using energy-guided flow matching

arXiv:2610.02232v1 Announce Type: cross Abstract: Predicting phenotypic and transcriptional responses to perturbations at single-cell resolution provides a powerful tool for probing biological systems

Harness-Aware Distillation for Small Language Model Agents

arXiv:2610.02858v1 Announce Type: new Abstract: Language model agents are deployed with a harness, the software around the model that manages its context, tools, and feedback. When such an agent is di

Local Ai

Harnessing LLMs as Agents: What Does It Cost?

arXiv:2610.02488v1 Announce Type: new Abstract: Language-model agents increasingly rely on harnesses that manage bounded context, persistent memory, tools, verification, and repeated execution, yet ex

local-aiarxiv-cs-lg

MEA: A Reward-Driven Multi-Agent System for Faithful Model Explanations

arXiv:2610.02480v1 Announce Type: new Abstract: Recent years have seen the employment of a plethora of machine learning (ML) models in high-stakes domains, but they remain largely opaque to the practi

Mind the Refinement Gap: When Safe High-Level Robot Plans Produce Unsafe Executions

arXiv:2610.02662v1 Announce Type: new Abstract: Language-enabled robot systems increasingly combine semantic-graph planning with temporal-logic safety monitors. We investigate a trace-completeness ass

safetyarxiv-cs-lg

OpenGameEval: Benchmarking Agentic Programming and Exploration in a Stateful Game Engine

arXiv:2610.02563v1 Announce Type: cross Abstract: We present OpenGameEval, a benchmark and evaluation framework for agentic game development inside Roblox Studio. It runs language models as agents in

Pincer: Resource Authorization for Agents using a Digital Twin

arXiv:2610.02569v1 Announce Type: cross Abstract: Coding agents have become increasingly long-horizon, autonomous, reliant on general-purpose shell and maintain their own persistent memory for self-im

Positive-Unlabeled Learning for Agent Safety False Alarm Auditing

arXiv:2610.02925v1 Announce Type: new Abstract: Safety monitors help safeguard language-model agents interacting with external tools and environments, but conservative monitoring can generate many fal

Predictively Oriented Gaussian Process Posteriors

arXiv:2610.03201v1 Announce Type: cross Abstract: Gaussian Processes (GPs) are a powerful tool for modelling and quantifying uncertainty in functional relationships. However, they require practitioner

RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer

arXiv:2610.02717v1 Announce Type: new Abstract: A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to con

safetyarxiv-cs-ro

ActiveSaddler: Automated Curriculum Learning for Agent Harness Optimization

arXiv:2610.00906v1 Announce Type: new Abstract: Automated harness optimization can substantially improve LLM agents by iteratively updating their prompts, tool interfaces, and control logic from execu

Are AI Coders Snitches? An Empirical Study of Pretraining Data Detection on Code Large Language Models

arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these mod

Deep Symmetric Autoencoders from the Eckart-Young-Schmidt Perspective

model-releasesarxiv-cs-lg

arXiv:2506.11641v2 Announce Type: replace-cross Abstract: Deep autoencoders have become a fundamental tool in various machine learning applications, ranging from dimensionality reduction and reduced o

Exploring Weaknesses of Generative Image Watermarks against Latent Frequency Masking

arXiv:2610.02010v1 Announce Type: cross Abstract: Invisible watermarking has become a central tool for tracing AI-generated images, but its robustness against adaptive removal attacks remains an open

researcharxiv-cs-ai

Graph Representation via Elements of Discrete Morse and Cobordism Theories

arXiv:2610.01937v1 Announce Type: new Abstract: Topology is, by its nature and design, suited to structure that is nonlinear, multiscale, and nonstationary - however, within machine learning, its use

MCRI: A Four-Dimensional Framework for Analyzing and Evaluating Agent Skills

arXiv:2610.01506v1 Announce Type: new Abstract: As agents evolve from single-tool systems into modular, composite architectures, skills are becoming an important mechanism for capability development a

Mimir: Physics-Grounded LLM Agents for Long-Horizon Irrigation Control

arXiv:2610.02038v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly combine reasoning, tool use, and action, but most evidence comes from episodic tasks with relatively imme

Proof-Gated Signing: Solver-Checked Transaction Guards that Hold Under State Drift for Onchain AI Agents

arXiv:2610.00354v1 Announce Type: cross Abstract: AI agents that control wallets read attacker-reachable content, so they can be steered into proposing harmful transactions. The usual last line of def

Reachability Is Not Generalization: Understanding Verb--Noun Decomposition in Assembly Action Recognition

arXiv:2610.00064v1 Announce Type: new Abstract: Assembly actions are compositional: they combine a manipulation with a part or tool. In deployment, systems routinely encounter novel combinations of fa

researcharxiv-cs-cv

REVEAL: Robust Evolution of Vision-Language Models for Explainable AI-Video Detection

model-releasesarxiv-cs-cv

arXiv:2502.14994v2 Announce Type: replace Abstract: The rapid advancement of AI-generated video poses challenges to digital authenticity and security. Current detection methods, often trained on speci

Trustworthy Data- and ML-Ops for Intelligent Transportation Systems and Logistics

arXiv:2610.01282v1 Announce Type: new Abstract: The rapid evolution of Intelligent Transportation Systems and Logistics (ITS&L) has become a cornerstone of the modern social economy, relying heavily o

YouRA: A Persistent-State Architecture for Evidence-Traceable Autonomous Research Agents

arXiv:2610.01097v1 Announce Type: new Abstract: End-to-end research agents can now produce complete scientific papers, yet manuscript claims often diverge from executed experiments. This gap is struct

A strategic roadmap for an atomistic machine-learning ecosystem

arXiv:2609.39090v1 Announce Type: cross Abstract: Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of m

Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration

arXiv:2603.01623v2 Announce Type: replace Abstract: Diffusion models have become the dominant tool for high-fidelity image and video generation, yet are critically bottlenecked by their inference spee

researcharxiv-cs-cv

Approval Laundering: Systematizing Approval--Execution Binding Failures in AI Coding-Agent Harnesses

arXiv:2609.38983v1 Announce Type: cross Abstract: Modern AI coding-agent harnesses (Claude Code, Codex CLI, Cursor) rest their security boundary on a largely unexamined assumption: that the action A a

Auditing Agent Actions through Query-Conditioned Attribution

arXiv:2609.33676v2 Announce Type: replace Abstract: LLM agents increasingly take consequential actions through interactions with users, policies, and external tools. Auditing these agents requires aut

Tutorials

CNCGEN: A Dataset and Framework for Machining Process Planning and Toolpath Generation from B-rep Models

arXiv:2609.39738v1 Announce Type: new Abstract: Learning to generate machining process plans and toolpaths from B-rep CAD requires coupling discrete operation decisions with continuous tool motion as

tutorialsarxiv-cs-lg

Composing Task-specific Agent Harnesses at Test Time with Reusable Primitives

arXiv:2609.38912v1 Announce Type: new Abstract: Agent harnesses govern how large language models (LLMs) gather context, invoke tools, verify results, preserve state, and terminate, largely affecting a

CompoWorld: Compositional Environment Scaling for General Agents

arXiv:2609.33665v2 Announce Type: replace Abstract: Automatically generated environments provide a scalable source of interaction data for training general agents. However, existing approaches mainly

Differentiable Expectation-Maximisation and Applications to Gaussian Mixture Model Optimal Transport

arXiv:2509.02109v3 Announce Type: replace Abstract: The Expectation-Maximisation (EM) algorithm is a central tool in statistics and machine learning, widely used for latent-variable models such as Gau

Drift Inspector: Exploring and Measuring Scientific Drift with Atomic Contribution Claims

model-releasesarxiv-cs-cl

arXiv:2609.39710v1 Announce Type: new Abstract: Scientific abstracts mix contributions with background, motivation, and meta-language, so tools that read them as-is cannot separate what a field produc

EvoSteer: Online Self-Evolving Graph Orchestration via Reference-Anchored Credit Assignment

arXiv:2609.38661v1 Announce Type: new Abstract: In recent years, LLM-based multi-agent systems have been widely applied to orchestrate tool-using agents into executable communication graphs. However,

GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives

arXiv:2609.39601v1 Announce Type: cross Abstract: Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fa

Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMs

arXiv:2609.38266v1 Announce Type: cross Abstract: Agentic large language models (LLMs) now move money through tools, yet the record of what they did is usually a trace their own process emits beside t

Right Answer, Wrong Mechanism: Detecting Pernicious Divergence in Causal Interventions

model-releasesarxiv-cs-lg

arXiv:2609.39243v1 Announce Type: new Abstract: Causal interventions such as activation patching and distributed alignment search (DAS) are the main tool for making mechanistic claims about neural net

Tutorials

Robust Budget Pacing with a Single Sample

arXiv:2302.02006v2 Announce Type: replace Abstract: Major Internet advertising platforms offer budget pacing tools as a standard service for advertisers to manage their ad campaigns. Given the inheren

tutorialsarxiv-cs-lg