Search: “tools”

arXiv:2609.11450v1 Announce Type: new Abstract: Background: To determine whether cross-lingual clinical annotation projection can be formulated as a text-preserving, document-level generative task tha

local-aiarxiv-cs-cl

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Safety

Do Agents Know When They Succeed? Calibrating Agent Confidence from Internal Representations

DGX agent

arXiv:2609.09448v1 Announce Type: new Abstract: As agentic systems getting adopted rapidly in safety critical applications, it is vital to measure the confidence associated with the agentic actions. I

safetyarxiv-cs-ai

11 Sept 2026

From Connectivity to Rewards: Dense Reward Learning with Directed State Graphs

arXiv:2609.10781v1 Announce Type: new Abstract: The integration of graphs with Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) has received increasing attention, as graphs naturally encod

safetyarxiv-cs-lg

General Quantification of Covariate and Concept Shifts

arXiv:2609.11918v1 Announce Type: new Abstract: Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, id

Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis

arXiv:2506.00849v2 Announce Type: replace Abstract: Despite the empirical success of Diffusion Models (DMs) and Variational Autoencoders (VAEs), their generalization performance remains theoretically

JarvisGUI: Towards Cross-Device GUI Agents with Dynamic Task Composition

arXiv:2609.10451v1 Announce Type: new Abstract: Real-world GUI usage frequently involves workflows that span multiple devices and platforms, requiring the transfer of intermediate results, maintenance

MC-DeTra: Motion-Consistent Joint Object Detection and Socially-Aware Trajectory Forecasting in Bird's-Eye-View Images

model-releasesarxiv-cs-cv

arXiv:2609.11717v1 Announce Type: new Abstract: Unified models for object detection and trajectory forecasting aim to merge perception and prediction for autonomous driving, refining actor trajectorie

On the Relation between Code Quality and Machine Learning Performance: A Large-scale Empirical Study

arXiv:2609.10610v1 Announce Type: cross Abstract: Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is oft

OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis

arXiv:2603.20278v2 Announce Type: replace-cross Abstract: Training deep research agents requires long-horizon trajectories that interleave search, evidence aggregation, and multi-step reasoning. Howev

agentsarxiv-cs-cl

Tutorials

Supply Chain Analytics: A Data-Driven Approach

arXiv:2609.10563v1 Announce Type: cross Abstract: Modern supply chain networks increasingly rely on real-time data to navigate structural uncertainties, market volatility, and operational disruptions.

tutorialsarxiv-cs-lg

SwarmNxt: Open-source Software-Hardware Platform for Fast and Agile Aerial Swarms

arXiv:2609.11382v1 Announce Type: new Abstract: Aerial robot swarms have the potential to transform time-critical safety, security, and search-and-rescue operations. By coordinating multiple robots, t

safetyarxiv-cs-ro

T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks

model-releasesarxiv-cs-lg

arXiv:2609.11042v1 Announce Type: new Abstract: Agent usage is shifting toward long-horizon tasks such as coding and scientific discovery, among which terminal tasks are especially important. We intro

The Era by Eon Benchmark: A Generated Enterprise Estate with Exact Ground Truth for Benchmarking LLM Agents

arXiv:2609.09853v1 Announce Type: new Abstract: LLM agents for enterprise systems of record cannot be evaluated on customer production data, and no existing substitute provides ground truth. We presen

Using Automated Vehicles Operational Data to Confirm Safety and Anticipate Threats

arXiv:2609.11549v1 Announce Type: new Abstract: European Union (EU) policymakers adopted revolutionary data collection provisions for Automated Driving Systems (ADS) in the recently approved regulatio

safetyarxiv-cs-ro

V-Retrver: Evidence-Driven Agentic Reasoning for Universal Multimodal Retrieval

arXiv:2602.06034v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have recently been applied to universal multimodal retrieval, where Chain-of-Thought (CoT) reasoning improv

agentsarxiv-cs-cv

Watermarks Without Verification: AI Text Watermarking After the EU AI Act

arXiv:2609.09604v1 Announce Type: cross Abstract: On August 2, 2026, the obligations of Article 50 of the EU AI Act took effect, requiring generative AI providers to mark the content their systems pro

A Data-Driven Framework for Identifying and Prioritizing RPA Opportunities in Healthcare Processes

arXiv:2609.09137v1 Announce Type: new Abstract: Robotic Process Automation (RPA) is widely used to reduce administrative burden in United States hospitals, yet an estimated 30-50% of RPA initiatives u

applicationsarxiv-cs-ai

Agentic ML Exploration (A-MLE) for Ads Ranking

arXiv:2609.08248v1 Announce Type: new Abstract: Modern industrial ads ranking stacks are increasingly bottlenecked not by model capacity or training compute, but by the throughput of human ML iteratio

AgentLeak: Cloning Stronger LLM Agent Capabilities onto Weaker Agents Beyond Skill Stealing

arXiv:2609.07131v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly achieve long-horizon tasks by combining foundation models with explicit skills and implicit procedural

agentsarxiv-cs-ai

An Explainable Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Using Molecular Descriptors

arXiv:2609.10012v1 Announce Type: new Abstract: Blood-brain barrier (BBB) permeability is a critical determinant in the development of central nervous system therapeutics because it directly influence

Arti-JEPA: Adapting Video World Model to Real-Time MRI of the Vocal Tract for Speech-Production Analysis

arXiv:2609.09757v1 Announce Type: cross Abstract: Real-time MRI (rtMRI) captures the dynamics of the entire vocal tract during speech, but labeled data are scarce and the modality - single-slice, gray

applicationsarxiv-cs-cv

AURA-Eval: Evaluation Framework for Acting Under Risk Awareness in LLM Agent Trajectories

arXiv:2609.06783v1 Announce Type: cross Abstract: LLM agents operate in workflows where unsafe actions can have real consequences. Existing safety evaluations often reduce behavior to a single score,

Automatic Reproducible Camera Intrinsic Calibration

model-releasesarxiv-cs-cv

arXiv:2609.10082v1 Announce Type: cross Abstract: Accurate camera intrinsic calibration is fundamental to robot perception, and the accuracy depends on the quality of the collected images. However, ex

Benchmarking Hybrid Deep Research Across Database Querying and Web Search

model-releasesarxiv-cs-cl

arXiv:2609.09410v1 Announce Type: new Abstract: While autonomous agents have made significant strides in 'deep research' by iteratively navigating the open web to synthesize information, real-world pr

Beyond Coherence: Benchmarking Professional Editing-Technique Execution in Multi-Shot Audio-Video Generation

arXiv:2609.08275v1 Announce Type: new Abstract: Recent multi-shot audio-video generators can produce increasingly coherent and cinematic outputs, but coherence does not imply the ability to execute ed

Beyond Final Decisions: A Process-Centric Benchmark for Transparent AI-Assisted Peer Review

arXiv:2609.05947v1 Announce Type: new Abstract: Peer review is central to quality control in science. However, existing evaluations of AI-assisted peer review mainly focus on the overall quality of ge

Building Trustworthy Graph-Agentic RAG for Social Good: Architectures, Failure Propagation, and Assurance by Construction

arXiv:2609.06391v1 Announce Type: new Abstract: Graph-agentic retrieval-augmented generation combines structured evidence with adaptive controllers that can plan retrieval, traverse relations, verify

agentsarxiv-cs-ai

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

Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

arXiv:2609.05779v1 Announce Type: cross Abstract: Large language models used for code editing can be trained and deployed in at least two output regimes: direct generation, where the model emits the e

Elsewise: Authoring Open-ended Interactive Narrative with Possibility Space Visualization

arXiv:2601.15295v2 Announce Type: replace-cross Abstract: Interactive narrative (IN) authors craft spaces of divergent narrative possibilities for players to explore, with the player's input determini

researcharxiv-cs-cl

Explainable Deep Learning for Price-Trade Dynamics: From Black-Box Forecasts to Effective Parametric Models

arXiv:2609.06085v1 Announce Type: cross Abstract: Understanding the joint dynamics of prices and trades is central to market microstructure, where returns and order flow interact through nonlinear and

From Monolithic Blending to Agentic Orchestration: Dynamic Response for Conversational Assistants at Scale

arXiv:2609.05758v2 Announce Type: new Abstract: Conversational assistants can blend retrieval, action selection, escalation, and wording in a single model path, or separate those roles. We report a pr

From Representation to Enactment: The ABC Framework of the Translating Mind

arXiv:2511.16811v2 Announce Type: replace Abstract: Building on the third-wave Extended Mind (EM) theory and radical enactivism, this article suggests an alternative to representation-based models of

researcharxiv-cs-cl

Gaussian Approximation for Multivariate Martingale Sums from Uniformly Ergodic Markov Chains

arXiv:2609.09480v1 Announce Type: cross Abstract: We develop Gaussian approximation bounds in higher-order Wasserstein distance W_p, pgeq2, for sums of multivariate martingale differences generated by

Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interaction

arXiv:2602.24080v3 Announce Type: replace Abstract: The pursuit of human-like conversational agents has long been guided by the Turing test. For modern speech-to-speech (S2S) systems, a critical yet u

researcharxiv-cs-ai

Intent Drift at SME Scale: Deployment Practice, Not Model Capability, Determines Agentic Compliance

arXiv:2609.05975v1 Announce Type: cross Abstract: We introduce Chain of Intent, a governance framework for agentic AI at small regulated firms, and validate it against a failure it was built to addres

KVShareArena: KV-Cache Reuse Across Contexts and Model Checkpoints

arXiv:2609.10266v1 Announce Type: new Abstract: LLM serving systems already reuse KV caches, but only when the reused text sits at the very start of the prompt. Two growing workloads break this condit

agentsarxiv-cs-cl

Local Ai

Localizing and Correcting Errors for LLM-based Planners

arXiv:2602.00276v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong reasoning capabilities on math and coding, but frequently fail on symbolic classical planning

local-aiarxiv-cs-ai

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

model-releasesarxiv-cs-cl

arXiv:2609.10016v1 Announce Type: cross Abstract: We introduce MetroLLM-Bench, a 955-case benchmark for testing language models as the policy layer of a transit kiosk. It covers six real metro systems

Optimal Value Inference for Reinforcement Learning

arXiv:2609.09981v1 Announce Type: cross Abstract: We study offline inference for the optimal value in reinforcement learning. Two new nuisances are derived as fixed points of a self-induced Bellman eq

safetyarxiv-cs-lg

Recovering Temporal and Geographic Signals from Language Model Embeddings

arXiv:2609.05721v1 Announce Type: new Abstract: Understanding whether language-model embeddings encode structured real-world information is important for both representation analysis and information r

applicationsarxiv-cs-ai

SchemeArena: Factorized Stress Testing of Scheming in LLM Agents

arXiv:2609.08126v1 Announce Type: new Abstract: We study scheming in LLM agents, in which agents covertly pursue misaligned goals. Our focus is to understand how scheming arises from the interaction o

Silent Revision: Measuring Undisclosed Change in the Safety Frameworks of Frontier AI Developers

arXiv:2609.08789v1 Announce Type: cross Abstract: Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous. The European Union and California

Solving versus Verifying: Catching Contradictions in Tax Reasoning Systems

arXiv:2609.05928v1 Announce Type: cross Abstract: Large language models now compute correct tax liabilities on over 90% of well-formed cases in statutory benchmarks, which makes them candidates for th

applicationsarxiv-cs-ai

Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms

model-releasesarxiv-cs-lg

arXiv:2609.10276v1 Announce Type: cross Abstract: This paper introduces an evolutionary computation approach for consensus in structural Bayesian Network (BN) fusion under the constraint of limited tr

The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies

arXiv:2609.05514v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents are increasingly used as proxies for human participants in social science research, yet it remains unclear wheth

The Surprising Effectiveness of Approximate Value Iteration in Self-Play

arXiv:2609.09094v1 Announce Type: new Abstract: Combining search with function approximation has driven major advances in game-playing programs, making self-play algorithms more competitive than ever.

researcharxiv-cs-ai

The Unreliable Progress Bar: Can LLM Agents Reliably Report Task Progress Throughout Execution?

arXiv:2609.08589v1 Announce Type: cross Abstract: Recent large language models can emit task-progress signals that agent frameworks use to decide whether a task should continue or stop, yet whether a