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Anaconda expands beyond Python with agent swarms and AI security testing

Artificial intelligence development firm Anaconda Inc. is enhancing its enterprise AI platform with tools to coordinate groups of AI agents, test their security and move applications into production.

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Assembling Insights for Agentic Machine Learning Engineering Systems

DGX agent

arXiv:2610.04927v1 Announce Type: cross Abstract: Agentic machine learning engineering (MLE) is an emerging AI4SE application for complex ML tasks and a step toward recursive self-improvement of AI sy

model-releasesarxiv-cs-lg

6 Oct 2026

CEENs: Causality-enforced evolutional networks for solving time-dependent partial differential equations

arXiv:2610.04405v1 Announce Type: new Abstract: Despite the growing popularity of physics-informed neural networks (PINNs), their applicability in the long-time integration of partial differential equ

safetyarxiv-cs-lg

Constrained Goal-directed Planar Graph Generation with Grammar-based Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2610.06244v1 Announce Type: new Abstract: Planar graphs are central to applications across science and engineering, yet existing generators provide limited support for goal-directed generation u

Continual Action Quality Assessment via Adaptive Manifold-Aligned Graph Regularization

arXiv:2510.06842v2 Announce Type: replace Abstract: Action Quality Assessment (AQA) quantifies human actions in videos, supporting applications in sports scoring, rehabilitation, and skill evaluation.

Differentially Private Mixing of Public Datasets Improves Private Learning

arXiv:2610.06636v1 Announce Type: new Abstract: Many machine learning applications involve sensitive data and therefore require training under differential privacy (DP). However, DP training often deg

Efficient Hierarchical Transformers for Representing Log Data

arXiv:2408.16803v2 Announce Type: replace Abstract: Transformers have gained widespread acclaim for their versatility in handling diverse data structures, yet their application to log data remains und

Evolutionary feature selection for spiking neural network pattern classifiers

arXiv:2604.26654v1 Announce Type: cross Abstract: This paper presents an application of the biologically realistic JASTAP neural network model to classification tasks. The JASTAP neural network model

From Kinematic Motion Planners to Dynamic Autonomous Navigation with Obstacle Avoidance (Extended version)

arXiv:2503.17589v3 Announce Type: replace Abstract: Kinematic motion planners are among the most widely used control approaches in robotic applications. By modeling the robot as a first-order system,

safetyarxiv-cs-ro

GFPack++: Attention-Driven Gradient Fields for Optimizing 2D Irregular Packing

arXiv:2406.07579v2 Announce Type: replace-cross Abstract: 2D irregular packing is a classic combinatorial optimization problem with various applications, such as material utilization and texture atlas

Imagine to Act: High-Fidelity Data Synthesis via Image Editing World Model for Scalable GUI Agent Training

arXiv:2610.05861v1 Announce Type: new Abstract: Graphical User Interface (GUI) agents have emerged as a promising paradigm for automating complex digital workflows across diverse applications. However

agentsarxiv-cs-cv

Kolmogorov-Arnold Networks for Personal Context Recognition on ExtraSensory

arXiv:2610.05250v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) have attracted increasing attention in recent years, with applications across a wide range of AI tasks. In this paper

Linear Bandits beyond Inner Product Spaces, the case of Bandit Optimal Transport

model-releasesarxiv-cs-lg

arXiv:2502.07397v3 Announce Type: replace-cross Abstract: Linear bandits have long been a central topic in online learning, with applications ranging from recommendation systems to adaptive clinical t

Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph

arXiv:2411.12426v3 Announce Type: replace Abstract: Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based

NM-LIO: Multiple LiDAR-Inertial Odometry Addressing LiDAR Measurement Noise Discrepancy

arXiv:2610.04551v1 Announce Type: new Abstract: Multiple LiDAR-inertial odometry methods have been widely applied in robotic applications owing to their enhanced accuracy and reliability. However, ado

researcharxiv-cs-ro

PB-STDG: A Prediction-Based Short-Term Decentralized Greedy Guidance Algorithm for a Drone Road System

arXiv:2610.05122v1 Announce Type: new Abstract: In recent years, Unmanned Aerial Vehicles (UAVs) or drones have been increasingly adopted in urban environments for applications such as parcel delivery

safetyarxiv-cs-ro

Quantifying the Stability of Multi-Step Reasoning via Error Amplification

arXiv:2610.06404v1 Announce Type: new Abstract: We consider the stability of multi-step reasoning processes, which have extensive applications in language models, including chain-of-thought and algori

Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries

arXiv:2208.08697v2 Announce Type: replace-cross Abstract: The security of deep learning (DL) systems is an extremely important field of study as they are being deployed in several applications due to

researcharxiv-cs-cv

Local Ai

RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers

arXiv:2610.04457v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections

local-aiarxiv-cs-cv

SO(3)-RoPE for Spherical Transformers

arXiv:2610.06229v1 Announce Type: new Abstract: Spherical data arise in many scientific applications. Often spherical transformers disregard the geometry of the underlying spherical domain, causing di

SPDAlign: Interpretable Riemannian Alignment for EEG Forward Modeling Shifts

arXiv:2610.06315v1 Announce Type: new Abstract: Electroencephalography (EEG) based brain-computer interfaces enable direct brain-to-device communication for applications such as rehabilitation and com

safetyarxiv-cs-lg

THYME: Temporal Hierarchical-Cyclic Interactivity Modeling for Video Scene Graphs in Aerial Footage

arXiv:2507.09200v2 Announce Type: replace Abstract: The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dyna

XS-VID: A Large-Scale Benchmark for Small Object Detection and Tracking in Videos

arXiv:2407.18137v2 Announce Type: replace Abstract: Small object detection and tracking in videos remain critical yet underexplored challenges in computer vision, particularly for applications such as

AgentTrap: Stateful Feedback Deception against Autonomous Penetration Testing Agents

arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def

agentsarxiv-cs-ai

AptMQL-Bench: From Text-to-SQL to Text-to-MQL via Access-Pattern Schema Design and Data-Preserving Migration

model-releasesarxiv-cs-cl

arXiv:2610.02770v1 Announce Type: new Abstract: Document databases such as MongoDB are core infrastructure for modern applications, and natural-language interfaces to them---text-to-MQL---would let no

Controllable Accent Normalization via Discrete Diffusion

arXiv:2603.14275v3 Announce Type: replace-cross Abstract: Existing accent normalization methods do not typically offer control over accent strength, yet many applications-such as language learning and

DEPICT: Scoring Text-to-Image Alignment by Answer Agreement

arXiv:2610.03617v1 Announce Type: new Abstract: Image-text alignment is a core problem in computer vision with applications in caption evaluation, hallucination detection, data curation, and the bench

safetyarxiv-cs-cv

Distributionally Robust Survival Models under Subpopulation Shift and Outlier Contamination

arXiv:2610.02868v1 Announce Type: cross Abstract: Learning robust survival models under distribution shift is an important but challenging problem in many applications. In heterogeneous populations, a

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

safetyarxiv-cs-ai

MintFlow: Minimal Trajectory Intervention for Constrained Flow Matching

arXiv:2610.02260v1 Announce Type: new Abstract: Flow matching models excel at generative modeling, and many downstream applications require their samples to satisfy prescribed constraints, such as obs

Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning

arXiv:2506.05937v3 Announce Type: replace-cross Abstract: Reliability of deep learning models is critical for deployment in high-stakes applications, where out-of-distribution or adversarial inputs ma

TSGuard: A Real-Time Framework for Detecting and Imputing Missing Data in Streaming Time Series

arXiv:2610.03147v1 Announce Type: cross Abstract: Streaming sensor applications routinely suffer from delayed or missing observations caused by faults, communication losses, or environmental interfere

When Predicting Nothing Beats SAM 3: Revisiting Evaluation in Video Object Segmentation

arXiv:2610.02946v1 Announce Type: new Abstract: Video Object Segmentation (VOS) in complex and long videos is increasingly important for real-world applications, where target objects often appear only

Syntheses

Synthesis: Arxiv-Cs-Cl

synthesisarxiv-cs-clauto-generated

Auto-generated synthesis of 10865 entries about arxiv-cs-cl

4 Oct 2026

Anti-Persona: Disrupting Unauthorized Identity Binding and Recognition in Personalized Vision--Language Models

arXiv:2610.01944v1 Announce Type: new Abstract: Few-shot personalization enables large vision--language models (LVLMs) to learn user-specific visual concepts for applications such as personalized retr

safetyarxiv-cs-cv

Designing for Interpretation Uncertainty: Architecture and Principles for Topological Learning Analytics Dashboards

arXiv:2610.01749v1 Announce Type: cross Abstract: Topological Data Analysis (TDA) offers novel methods for understanding temporal dynamics in complex systems, yet its application in information system

Local Ai

Enterprise Representation Simplification (ERS): Reducing Representational Complexity for Enterprise AI

arXiv:2610.00791v1 Announce Type: new Abstract: Enterprise information is represented through artifacts shaped by applications, projects, technologies, organizational boundaries, and local requirement

local-aiarxiv-cs-ai

EyeTAG: Eye Trajectory-Aware Gaze Estimation

arXiv:2610.00922v1 Announce Type: new Abstract: Gaze estimation under natural head-eye motion underpins applications from driver monitoring to human-computer interaction. Single-frame methods predict

safetyarxiv-cs-cv

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

Learned End-to-End Guidance Schedules for Diffusion Models

arXiv:2610.01502v1 Announce Type: new Abstract: Diffusion models are a powerful generative paradigm used across multimedia and scientific applications. Guided diffusion methods impose requirements on

MemFit: Efficient Long-Term Agentic Memory

arXiv:2610.00872v1 Announce Type: new Abstract: Long-term memory systems for large language models (LLMs) have gained popularity for extending reasoning capabilities across applications. Current memor

agentsarxiv-cs-ai

Network World Models as Environments for Algorithm Design on Complex Systems

model-releasesarxiv-cs-ai

arXiv:2610.01048v1 Announce Type: new Abstract: World models, which simulate an environment and predict how it changes under actions, are increasingly used in real-world applications such as robotics.

Ontology-Grounded, Reasoner-Verified Benchmarks for Evaluating LLM Reasoning in Scientific AI

arXiv:2610.00682v1 Announce Type: new Abstract: Large language models (LLMs) increasingly underpin scientific AI applications that reason over structured knowledge, from biomedical question answering

Rethinking Data Augmentation under Covariate Shift: Invariant-Guided Diffusion and Prototype Reweighting

arXiv:2610.00873v1 Announce Type: cross Abstract: In many industrial applications, 1) tabular data is scarce and imbalanced and thus requires synthetic expansion; 2) input distributions drift between

Local Ai

Sample complexity bounds for categorical Markov random fields via Discrete Diffusions

arXiv:2610.02128v1 Announce Type: cross Abstract: Many applications in statistics, economics, and physics require sampling from high-dimensional categorical distributions with local dependence structu

local-aiarxiv-cs-lg

Scores That Hold, Benchmarks That Leak: Measuring Dataset Contamination in Public Brain-Tumor MRI Classification

model-releasesarxiv-cs-ai

arXiv:2610.00421v1 Announce Type: cross Abstract: Automated classification of brain tumors from MRI is a heavily published application of deep learning in medical imaging, with reported accuracies on

Uncertainty-Aware Learning from Multi-Expert Interval Targets

arXiv:2610.00102v1 Announce Type: new Abstract: Many machine learning (ML) applications rely on expert labels, and qualified experts may provide different but plausible interpretations of the same obs

UrbanVLA: A Vision-Language-Action Model for Urban Micromobility

arXiv:2510.23576v2 Announce Type: replace-cross Abstract: Urban micromobility applications, such as delivery robots, demand reliable navigation across large-scale urban environments while following lo

safetyarxiv-cs-ai