Search: “tools”

arXiv:2508.09320v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) are increasingly often employed in high-stakes applications, such as fraud detection or healthcare, but are susce

applicationsarxiv-cs-ai

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Agents

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition

DGX agent

arXiv:2605.13193v1 Announce Type: new Abstract: Fine-grained recognition in everyday life is often not a closed-book classification problem: when encountering unfamiliar objects, humans actively searc

agentsarxiv-cs-cv

14 May 2026

High-Dimensional Analysis of Bootstrap Ensemble Classifiers

arXiv:2505.14587v2 Announce Type: replace-cross Abstract: Bootstrap methods have long been the cornerstone of ensemble learning in machine learning. This paper presents a theoretical analysis of boots

ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks

arXiv:2605.12768v1 Announce Type: cross Abstract: Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains underserved. We introduce

Local Ai

Kernel Embeddings and the Separation of Measure Phenomenon

arXiv:2505.04613v4 Announce Type: replace-cross Abstract: We prove that kernel covariance embeddings lead to information-theoretically perfect separation of distinct continuous probability distributio

local-aiarxiv-cs-lg

Language-Based Agent Control

arXiv:2605.12863v1 Announce Type: cross Abstract: This paper introduces language-based agent control (LBAC), a new programming model for agentic applications that brings techniques from programming la

Large Language Models Lack Temporal Awareness of Medical Knowledge

arXiv:2605.13045v1 Announce Type: new Abstract: The existing methods for evaluating the medical knowledge of Large Language Models (LLMs) are largely based on atemporal examination-style benchmarks, w

LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving

model-releasesarxiv-cs-ai

arXiv:2605.13137v1 Announce Type: cross Abstract: Proving theorems in Lean 4 often requires identifying a scattered set of library lemmas whose joint use enables a concise proof -- a task we call glob

Learning POMDP World Models from Observations with Language-Model Priors

arXiv:2605.13740v1 Announce Type: new Abstract: Whether navigating a building, operating a robot, or playing a game, an agent that acts effectively in an environment must first learn an internal model

agentsarxiv-cs-lg

Mixed neural posterior estimation for simulators with discrete and continuous parameters

arXiv:2605.13551v1 Announce Type: new Abstract: Neural Posterior Estimation (NPE) enables rapid parameter inference for complex simulators with intractable likelihoods. NPE trains an inference network

Multi-Agent Systems in Emergency Departments: Validation Study on a ED Digital Twin

arXiv:2605.13345v1 Announce Type: new Abstract: Emergency departments (ED) face challenges in patient care and resource management. We propose to explore optimization strategies in a realistic and fle

Multi-Rollout On-Policy Distillation via Peer Successes and Failures

arXiv:2605.12652v1 Announce Type: cross Abstract: Large language models are often post-trained with sparse verifier rewards, which indicate whether a sampled trajectory succeeds but provide limited gu

safetyarxiv-cs-ai

Parallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction

arXiv:2605.12683v1 Announce Type: cross Abstract: Reconstructing nonlinear dynamical systems (DS) from data (DSR) is a fundamental challenge in science and engineering, but it inherently relies on seq

Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach

arXiv:2605.13830v1 Announce Type: new Abstract: Decision tree ensembles (DTE) are a popular model for a wide range of AI classification tasks, used in multiple safety critical domains, and hence verif

safetyarxiv-cs-ai

RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records

arXiv:2507.15867v2 Announce Type: replace-cross Abstract: Rare diseases affect 1 in 10 Americans yet remain systematically underdocumented in clinical records. ICD-based systems cannot capture their b

Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes

arXiv:2605.13591v1 Announce Type: new Abstract: Reliable autonomous driving relies on large-scale, well-labeled data and robust models. However, manual data collection is resource-intensive, and tradi

safetyarxiv-cs-cv

Applications

Representing Higher-Order Networks: A Survey of Graph-Based Frameworks

arXiv:2605.12509v1 Announce Type: cross Abstract: Many real-world phenomena are naturally modeled by graphs and networks. However, classical graph models are often limited to pairwise interactions and

applicationsarxiv-cs-ai

Tutorials

Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation

arXiv:2605.12975v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a standard approach for knowledge-intensive question answering, but existing systems remain brittle on m

tutorialsarxiv-cs-ai

RTLC -- Research, Teach-to-Learn, Critique: A three-stage prompting paradigm inspired by the Feynman Learning Technique that lifts LLM-as-judge accuracy on JudgeBench with no fine-tuning

model-releasesarxiv-cs-ai

arXiv:2605.13695v1 Announce Type: cross Abstract: LLM-as-a-judge is now the default measurement instrument for open-ended generation, but on the public JudgeBench benchmark even strong instruction-tun

scShapeBench: Discovering geometry from high dimensional scRNAseq data

arXiv:2605.12662v1 Announce Type: new Abstract: High-dimensional point cloud data arise across many scientific domains, especially single-cell biology. The shapes or topologies of these datasets deter

Sharpness-Guided Group Relative Policy Optimization via Probability Shaping

arXiv:2511.00066v4 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a practical route to improve large language model reasoning, and Group Relative Pol

Small Area Estimation of Case Growths for Timely COVID-19 Outbreak Detection

arXiv:2312.04110v2 Announce Type: replace-cross Abstract: The COVID-19 pandemic has exerted a profound impact on the global economy and continues to exact a significant toll on human lives. The COVID-

Spectral Energy Centroid: a Metric for Improving Performance and Analyzing Spectral Bias in Implicit Neural Representations

arXiv:2605.12709v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) model continuous signals using multilayer perceptrons (MLPs), enabling compact, differentiable, and high-fidelity

Still Camouflage, Moving Illusion: View-Induced Trajectory Manipulation in Autonomous Driving

arXiv:2605.12743v1 Announce Type: cross Abstract: Existing physical adversarial attacks on vision-based autonomous driving induce time-evolving perception errors, including biased object tracking or t

agentsarxiv-cs-cv

The Payment Heterogeneity Index: An Integrated Unsupervised Framework for High-Volume Procurement Oversight and Decision Support

arXiv:2605.12547v1 Announce Type: cross Abstract: Public procurement is vulnerable to error, fraud and corruption, yet high transaction volumes overwhelm oversight. While research often focuses on ten

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery

arXiv:2605.12784v1 Announce Type: new Abstract: Advances in large language models (LLMs) have recently opened new and promising avenues for small-molecule drug discovery. Yet existing LLM-based approa

agentsarxiv-cs-lg

Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context

arXiv:2605.13831v1 Announce Type: new Abstract: Long-context modeling is becoming a core capability of modern large vision-language models (LVLMs), enabling sustained context management across long-do

agentsarxiv-cs-cv

Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics

arXiv:2402.15415v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) is the dominant parameter-efficient fine-tuning method due to its favorable compute-performance trade-off, yet it suffers

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone

arXiv:2605.11405v1 Announce Type: new Abstract: Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language model

A categorical error sensitivity index (ISEC): A preventive ordinal decision-support measure for irrecoverable errors in manual data entry systems

arXiv:2605.12328v1 Announce Type: new Abstract: Data entry systems remain structurally vulnerable to categorical misclassifications, particularly in small and medium sized enterprises (SMEs). When nom

researcharxiv-cs-cl

Acceleration of horizontal numerical advection for atmospheric modeling through surrogate modeling with temporal coarse-graining

arXiv:2605.10956v1 Announce Type: cross Abstract: Machine-learned surrogate modeling of advection may accelerate geoscientific models, but existing approaches have either achieved limited speedup or h

Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts

arXiv:2605.12375v1 Announce Type: new Abstract: Accurate crop yield forecasting in commercial soft fruit production is constrained by the data available in typical commercial farm records, which lack

Beyond Prediction: Interval Neural Networks for Uncertainty-Aware System Identification

arXiv:2605.11460v1 Announce Type: new Abstract: System identification (SysID) is critical for modeling dynamical systems from experimental data, yet traditional approaches often fail to capture nonlin

CAD-feature enhanced machine learning for manufacturing effort estimation on sheet metal bending parts

model-releasesarxiv-cs-cv

arXiv:2605.12266v1 Announce Type: new Abstract: Graph-based machine learning has emerged as a promising approach for manufacturability analysis by learning directly from CAD models represented as Boun

CTFusion: A CTF-based Benchmark for LLM Agent Evaluation

arXiv:2605.11504v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems for complex, multi-step tasks; cybersecurity is emerging as a prominent app

DeconDTN-Toolkit: A Library for Evaluation and Enhancement of Robustness to Provenance Shift

arXiv:2605.11237v1 Announce Type: new Abstract: Despite the burgeoning body of work on distribution shifts, provenance shift-where the relationship between data source and label changes at deployment-

DiffScore: Text Evaluation Beyond Autoregressive Likelihood

model-releasesarxiv-cs-cl

arXiv:2605.11601v1 Announce Type: new Abstract: Autoregressive language models are widely used for text evaluation, however, their left-to-right factorization introduces positional bias, i.e., early t

DIPSER: A Dataset for In-Person Student Engagement Recognition in the Wild

arXiv:2502.20209v3 Announce Type: replace Abstract: In this paper, a novel dataset is introduced, designed to assess student attention within in-person classroom settings. This dataset encompasses RGB

researcharxiv-cs-cv

Tutorials

FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models

arXiv:2605.11527v1 Announce Type: new Abstract: Diffusion models are the leading approach for tabular data synthesis and are increasingly used to share sensitive records. Whether they actually protect

tutorialsarxiv-cs-lg

Applications

Fractal Graph Contrastive Learning

arXiv:2505.11356v4 Announce Type: replace Abstract: Graph Contrastive Learning (GCL) relies on semantically consistent graph augmentations, but common local perturbations provide limited control over

applicationsarxiv-cs-lg

From Generic Correlation to Input-Specific Credit in On-Policy Self Distillation

arXiv:2605.11613v1 Announce Type: new Abstract: On-policy self-distillation has emerged as a promising paradigm for post-training language models, in which the model conditions on environment feedback

GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation

arXiv:2605.11853v1 Announce Type: cross Abstract: Reinforcement learning has become a widely used post-training approach for LLM agents, where training commonly relies on outcome-level rewards that pr

safetyarxiv-cs-cl

HE-SNR: Uncovering Latent Logic via Entropy for Guiding Mid-Training on SWE-bench

model-releasesarxiv-cs-cl

arXiv:2601.20255v2 Announce Type: replace-cross Abstract: SWE-bench has emerged as the premier benchmark for evaluating Large Language Models on complex software engineering tasks. While these capabil

INSANE: Cross-Domain UAV Data Sets with Increased Number of Sensors for developing Advanced and Novel Estimators

arXiv:2210.09114v2 Announce Type: replace Abstract: For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic enviro

agentsarxiv-cs-ro

Intention-Conditioned Flow Occupancy Models

arXiv:2506.08902v4 Announce Type: replace Abstract: Large-scale pre-training has fundamentally changed how machine learning research is done today: large foundation models are trained once, and then c

Model-based Bootstrap of Controlled Markov Chains

arXiv:2605.12410v1 Announce Type: cross Abstract: We propose and analyze a model-based bootstrap for transition kernels in finite controlled Markov chains (CMCs) with possibly nonstationary or history

Multi-Stream LLMs: Unblocking Language Models with Parallel Streams of Thoughts, Inputs and Outputs

arXiv:2605.12460v1 Announce Type: cross Abstract: The continued improvements in language model capability have unlocked their widespread use as drivers of autonomous agents, for example in coding or c

agentsarxiv-cs-cl

Principled Design of Diffusion-based Optimizers for Inverse Problems

arXiv:2605.11506v1 Announce Type: new Abstract: Score-based diffusion models achieve state-of-the-art performance for inverse problems, but their practical deployment is hindered by long inference tim

researcharxiv-cs-cv