Search: “software”

The reach of a verification tool decides its value: A controlled study of verification surface, artifact quality, and cost in AI coding agents

arXiv:2608.28795v1 Announce Type: cross Abstract: Modern artificial-intelligence coding agents can be equipped with tools for checking their own work e.g. a linter, a boot probe, a shell, a screenshot

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Model Releases

Towards a Systems Foundation for Agentic Skills: Architecture, Lifecycle, and Security

DGX agent

arXiv:2608.29596v1 Announce Type: new Abstract: Autonomous large language model (LLM) agents increasingly face reliability, context consumption, and execution stability bottlenecks when deployed on co

model-releasesarxiv-cs-ai

1 Sept 2026

TriPilot-FF: Coordinated Whole-Body Teleoperation with Force Feedback

arXiv:2602.09888v2 Announce Type: replace Abstract: Mobile manipulators broaden the operational envelope for robot manipulation. However, the whole-body teleoperation of such robots remains a problem:

safetyarxiv-cs-ro

Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection

arXiv:2503.11841v2 Announce Type: replace-cross Abstract: Machine Learning (ML) malware detectors rely heavily on crowd-sourced AntiVirus (AV) labels, with platforms like VirusTotal serving as trusted

Verification abundance, adjudication scarcity: what happens to mathematical knowledge when proof checking becomes free

arXiv:2608.28997v1 Announce Type: new Abstract: In May 2026 an OpenAI model produced a counterexample to the Erdos unit distance conjecture. Five mathematicians published a human-verified version the

researcharxiv-cs-ai

Which LLM for Which Work? Budgeted Model Allocation under Uncertain Evaluation

arXiv:2608.29560v1 Announce Type: new Abstract: A company with a fixed artificial intelligence (AI) budget must decide which large language model (LLM) handles each recurring workload. What it lacks i

safetyarxiv-cs-lg

RealSWE: A Compositional Evaluation of Coding Agents under Realistic User Requests

model-releasesarxiv-cs-lg

arXiv:2608.27831v1 Announce Type: cross Abstract: Coding agents are now commonly evaluated on the SWE-bench family of benchmarks, whose tasks are built from curated GitHub issues--long, structured, an

31 Aug 2026

MACGen: Toward Functionally Correct and Secure Code Generation via Multi-Agent Collaboration

arXiv:2608.25457v2 Announce Type: replace-cross Abstract: Despite their strong ability to generate code, large language models often fail to produce secure code, as their outputs frequently contain se

Prompt Sensitivity of Generative Agents: Evidence from an Epidemic Model

arXiv:2608.26221v1 Announce Type: cross Abstract: As generative AI gains traction, researchers are investigating its potential to serve as proxies for humans. From undergoing cognitive psychology expe

Stack Trace-Based Crash Deduplication with Transformer Adaptation

arXiv:2508.19449v2 Announce Type: replace-cross Abstract: Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer wo

safetyarxiv-cs-lg

Local Ai

Toward all-optical unsupervised Hebbian learning in deep photonic neuromorphic networks

arXiv:2601.22300v4 Announce Type: replace-cross Abstract: We propose a deep photonic neuromorphic network (PNN) architecture based on phase-change material (PCM) synapses and local optical feedback fo

local-aiarxiv-cs-lg

CropCop: An Auditable 120-Class Plant-Health Model from Benchmark Reconstruction to a Quantised Runtime Artifact

model-releasesarxiv-cs-cv

arXiv:2608.25539v1 Announce Type: new Abstract: A plant-health score can appear precise while resting on duplicated image families, a long-tailed label space, or a runtime file that was never evaluate

Lowering the Barrier to AI-Driven Inspection: A No-Code Workflow for Automated Structural Defect Detection

arXiv:2608.25176v1 Announce Type: new Abstract: Structural health monitoring (SHM) is essential in modern engineering, providing data for condition-based maintenance, lifecycle assessment, and predict

researcharxiv-cs-cv

One Policy, Many Embodiments: Unified Camera-Centric Action Geometry Pre-training for Heterogeneous Embodied Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.26058v1 Announce Type: new Abstract: Scaling generalist vision-language-action (VLA) policies is severely bottlenecked by the inherent heterogeneity of embodied data, which spans diverse ro

Hardware

TOPAS: Workflow-Aware Prefix-State Scheduling for Multi-Agent LLM Serving

arXiv:2608.25523v1 Announce Type: new Abstract: Prefix caching introduces a fundamental tradeoff in multi-agent large language model (LLM) serving: retaining a long system-prompt key-value (KV) cache

hardwarearxiv-cs-cl

Why and When Neural Networks Improve Local Approximation in Optimization

model-releasesarxiv-cs-lg

arXiv:2608.24963v1 Announce Type: new Abstract: Published experience with neural surrogates in derivative-free optimisation is contradictory: the same family of models that cuts the evaluation count o

AI Agents Push Humans Out of the Loop

arXiv:2608.23642v1 Announce Type: new Abstract: AI agents pose significant risks as they are granted increasing autonomy. A commonly proposed solution is human oversight and keeping a ''human in the l

Beyond Executable Models: The Pufibara Agent Harness and the Modelica Agent Workflow Benchmark for Physical System Modeling

arXiv:2608.23653v1 Announce Type: cross Abstract: AI agents are increasingly used for simulation-driven engineering. Physical system modeling presents different requirements from general-purpose code

Differential Learning for Robust Prediction of Thermal Stability with Application to Energetic Materials

arXiv:2608.23874v1 Announce Type: cross Abstract: Predicting thermal stability during handling and storage is essential for the design of safe and reliable energetic materials. However, experimental m

safetyarxiv-cs-lg

From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs

arXiv:2506.13182v3 Announce Type: replace-cross Abstract: [...] Since then, various APR approaches, especially those leveraging the power of large language models (LLMs), have been rapidly developed t

QABBA: Error-Guaranteed Symbolic Time-Series Compression via Integer-Quantized Aggregation

model-releasesarxiv-cs-lg

arXiv:2411.15209v3 Announce Type: replace Abstract: The expansion of time-series data from sensors and monitoring systems has made compact representations increasingly important. Such representations

Robust Slip Detection and Material Classification via Spatiotemporal Transformers on a Uniformly-Illuminated Visuo-Tactile Sensor

arXiv:2608.24162v1 Announce Type: new Abstract: Tactile sensing is central to robotic manipulation, among which slip detection stands out as a quintessential and critical task. However, existing slip

researcharxiv-cs-ro

ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability

arXiv:2608.23297v1 Announce Type: cross Abstract: Data assimilation (DA) is an essential tool for prediction and understanding in the geosciences. DA combines simulation programs representing scientif

Data-Driven Dynamic Algorithm Dispatch with Large Language Models

arXiv:2608.21584v1 Announce Type: new Abstract: We introduce a large language model (LLM)-driven approach for generating dynamic algorithmic dispatch heuristics in high-performance linear algebra. By

Decision-Support and Modeling with Large Language Models for Geothermal Well Arrays

arXiv:2608.22068v1 Announce Type: new Abstract: Geothermal well arrays, which organize multiple geothermal wells into carefully planned geometric configurations, provide opportunities to enhance energ

MCP-Universe RL: A Framework for Training MCP Tool-Use Agents via Reinforcement Learning

arXiv:2608.22167v1 Announce Type: new Abstract: Reinforcement learning (RL) has become an effective way to improve the tool-use ability of large language models (LLMs), but most existing RL frameworks

safetyarxiv-cs-ai

Mining Artifacts in Mycelium SEM Micrographs

arXiv:2103.07573v2 Announce Type: replace-cross Abstract: Mycelium is a promising biomaterial based on fungal mycelium, a highly porous, nanofibrous structure. Scanning electron micrographs are used t

researcharxiv-cs-cv

Particle Image Velocimetry Refinement via Consensus ADMM for Active Fluid Control

arXiv:2512.11695v3 Announce Type: replace-cross Abstract: Particle Image Velocimetry (PIV) is among the central modalities for measuring flow fields across laboratory, industrial and environmental set

agentsarxiv-cs-cv

Power-Performance Characterization of TinyML Systems

arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr

researcharxiv-cs-ai

Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol

arXiv:2608.21417v1 Announce Type: new Abstract: Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based work

Hardware

SweepLSD: A One-Pass, O(width)-Memory Line Segment Detector with an Integer-Only Streaming Core and a Real-Time FPGA Realization

arXiv:2608.22086v1 Announce Type: cross Abstract: We present SweepLSD, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the

hardwarearxiv-cs-cv

Walking on the DARKSIDE

arXiv:2608.23370v1 Announce Type: new Abstract: Large Language Models (LLMs) recognise patterns but do not natively track the path of exclusions that a coherent discourse demands. When an input rests

AgentDecarbonizer: Carbon-Aware Execution for AI Agents

arXiv:2608.20566v1 Announce Type: new Abstract: AI agents extend large language models from single prompt-response interactions to long-running, goaldirected workflows that issue many model calls, inv

agentsarxiv-cs-lg

Amplifying the imaging power of digital sky surveys with space telescopes data and generative AI

arXiv:2608.20666v1 Announce Type: cross Abstract: While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that

researcharxiv-cs-ai

Bern2Edge: A Neurosymbolic Compiler for Edge Deployment via Bernstein Polynomial Networks

arXiv:2608.20497v1 Announce Type: new Abstract: Deploying high-accuracy neural networks on resource-constrained edge devices remains challenging, as existing approaches treat training, compression, an

Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI

arXiv:2411.08881v3 Announce Type: replace-cross Abstract: AI-based systems, including Large Language Models (LLMs), impact millions by supporting diverse tasks but face issues like misinformation, bia

safetyarxiv-cs-ai

Event-triggered Implicit Perturbation for Zeroth-Order Fine-Tuning of Spiking Transformers

arXiv:2608.21223v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization estimates gradients using only forward-pass evaluations, making it suitable for fine-tuning non-differentiable, event-d

Applications

Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study

arXiv:2608.20406v1 Announce Type: new Abstract: Public health forecasts must respond to abrupt changes in surveillance data without over-extrapolating noise, reporting artifacts, or temporary trends.

applicationsarxiv-cs-lg

PrimeAgentOrchestrator: Memory-Primed Agent Spawning for Personal AI Infrastructure

arXiv:2608.20342v1 Announce Type: new Abstract: Large language model (LLM) coding agents start each session with an empty context window, discarding accumulated knowledge from prior work. We present P

SEISMO: Explanation-Aware, Trajectory-Conditioned LLM Agents for Sample-Efficient Molecular Optimisation

arXiv:2602.00663v3 Announce Type: replace Abstract: Optimizing molecules to achieve desired properties is a central bottleneck across the chemical sciences, particularly in the pharmaceutical industry

Testing and Evaluation of Agentic AI Systems In Military Command and Control

arXiv:2608.20597v1 Announce Type: cross Abstract: Agentic AI systems are being procured for military command and control (C2) under public commitments to rigorous testing and human oversight. Whether

Trustworthy RAG: An Evaluation Agent for Detecting Misinformation and Knowledge Poisoning in Generative AI Systems

arXiv:2608.21095v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) outputs in external knowledge, but RAG systems usually trust whatever they ret

Accelerated Genetic Programming Hyper-Heuristics for Simulation-Based Scheduling via Agentic AI

arXiv:2608.19487v1 Announce Type: cross Abstract: Python is widely used in scientific research because it enables rapid development and provides rich ecosystems for data analysis, artificial intellige

Better Call Graphs: A New Dataset of Function Call Graphs for Malware Classification

arXiv:2512.20872v2 Announce Type: replace-cross Abstract: Function call graphs (FCGs) have emerged as a powerful abstraction for malware detection, capturing the behavioral structure of applications b

agentsarxiv-cs-lg

MidTool: Mid-training Data Synthesis for Agentic Tool Use

arXiv:2608.20314v1 Announce Type: new Abstract: Mid-training is increasingly recognized as a critical stage for shaping the capabilities of large language models. Recent work has shown that targeted m

Tutorials

Specification-delta-driven data governance: an empirical study of the {guillemotleft}spec-delta{guillemotright} as the unit of change in lakehouse data platforms

arXiv:2608.19838v1 Announce Type: new Abstract: Spec Driven Development SDD has consolidated the idea that the specification rather than the code should be the primary artefact governing AI assisted w

tutorialsarxiv-cs-ai

Hardware

TorchDCM: A Unified PyTorch-Native Package for Discrete Choice Modeling

arXiv:2608.19231v1 Announce Type: cross Abstract: Estimating large and simulation-intensive discrete choice models (DCMs) requires repeated evaluation of utilities, probabilities, derivatives, and sim

hardwarearxiv-cs-lg

Adversarial Review: Structured Disagreement for Grounded Agentic Code Review

arXiv:2608.18167v1 Announce Type: new Abstract: Early multi-agent LLM systems often used role-separated teams, yet scaling agent count yields diminishing returns on repository-level coding tasks. Rece