Search: “engineering”

GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed

arXiv:2609.39600v1 Announce Type: cross Abstract: Autoregressive (AR) grounding models serialize spatial predictions, introducing sequential latency and imposing a causal order on output tokens. We vi

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

DGX agent

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

agentsarxiv-cs-ai

1 Oct 2026

Inference-Layer Security: Defending Against Adversarial Inference and Infrastructure Abuse

arXiv:2609.38239v1 Announce Type: cross Abstract: A Technical Report: Operating a large language model (LLM) as a service requires more than inference infrastructure: the provider must also defend aga

Tutorials

Introduction to Computer Vision

arXiv:2609.39627v1 Announce Type: new Abstract: This book presents a code-first introduction to computer vision, spanning classical 2D image processing, classical 3D vision, and deep learning. Organiz

tutorialsarxiv-cs-cv

Learning When and How to Intervene: A Hindsight-Distilled Sentinel for Coding Agents

arXiv:2609.39957v1 Announce Type: cross Abstract: Coding agents solve repository-level tasks through sequences of actions, where a single erroneous action can misdirect subsequent decisions and increa

PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn Agents

arXiv:2609.40285v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach for training language agents, providing dense teacher supervision on student-generated trajectories

Provably Tractable NFA-Constrained Language Generation via HMMs

arXiv:2609.40185v1 Announce Type: new Abstract: Constrained generation aims to sample from language models (LMs) conditioned on hard constraints. Existing constrained-generation techniques for nondete

researcharxiv-cs-cl

QATFactory: A Versatile, Deployment-Aligned Framework for Quantization-aware Training and Distillation of LLMs

arXiv:2609.39223v1 Announce Type: new Abstract: Large language model (LLM) inference is increasingly moving toward lower precision to realize the throughput of hardware accelerators, but aggressive po

RainAtlas: A Multi-Continental Dataset for Precipitation Downscaling

arXiv:2609.39833v1 Announce Type: new Abstract: Extreme rainfall events are increasing in intensity and frequency as climate change accelerates. While kilometer-scale precipitation forecasts are criti

Raw Imagery Impacting Your AI: Should You Care?

arXiv:2609.38265v1 Announce Type: cross Abstract: Onboard AI is gaining interest for space applications such as vessel, wildfire, and cloud detection, where real-time processing can improve mission re

researcharxiv-cs-ai

RefCon: Iterative Refinement and Contrastive Memory Extraction for Context-Evolving Agent

arXiv:2609.39143v1 Announce Type: new Abstract: Long-horizon agent interactions generate useful but noisy experience, and retraining models to absorb it is expensive. Context-evolving agents therefore

RSIGame: Autonomous Agentic Game Development with Recursive Self-improvement

model-releasesarxiv-cs-cl

arXiv:2609.39045v1 Announce Type: new Abstract: Recent advances in large language models have made automatic game generation increasingly feasible, yet reliably improving generated games beyond a play

Self-Evolving Algorithm-Design Agents: Escaping In-Context Evolutionary Stagnation via Population-Curated Policy Optimization

arXiv:2609.38757v1 Announce Type: new Abstract: Large language models are increasingly participating in complex real-world tasks in the form of algorithm-design agents, designing and refining algorith

Hardware

Sparse-WAM: Accelerating World Action Models via Action-Guided Sparse Imagination

arXiv:2609.38984v1 Announce Type: cross Abstract: World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and

hardwarearxiv-cs-ai

SteerQuant: Steering Quantization Error with Action-Guided Scaling in World-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.39056v1 Announce Type: new Abstract: World-action models (WAMs) jointly generate future world states and actions through iterative denoising, using shared weights to process heterogeneous s

Superficial Reflection or Genuine Thought? A Fine-Grained Cognitive Analysis of Large Reasoning Models

arXiv:2512.00729v2 Announce Type: replace Abstract: Motivated by the observed human-like behaviours in Large Reasoning Models (LRMs), this paper introduces a comprehensive taxonomy to characterise ato

researcharxiv-cs-ai

Synthesis Without Training: An Inference-Only Pipeline for Tabular, Temporal, and Relational Synthetic Data

arXiv:2609.38414v1 Announce Type: new Abstract: Synthetic data generation is dominated by the fit-then-sample paradigm: a generative model is trained on a private dataset and then sampled from. Despit

agentsarxiv-cs-lg

Turbo Harness: Instance-Adaptive Harness Optimization

arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty

Validity-Preserving Hierarchical RL for Joint Routing and Switch Placement in EDA

arXiv:2609.39749v1 Announce Type: new Abstract: Routing and switch placement are fundamental combinatorial optimization problems in chip design, requiring the joint optimization of routing topology an

researcharxiv-cs-lg

VAmoS Part Deux: Harder, More Realistic Voice-Agent Simulation

arXiv:2609.38512v1 Announce Type: new Abstract: Voice agents in production must handle several requests, background speech, and customers who lose patience. We introduce VAmoS Energy, a benchmark that

WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents

arXiv:2609.40325v1 Announce Type: new Abstract: As interactive 3D worlds are increasingly used to study intelligent behavior, it becomes important to develop efficient pipelines for identifying anomal

Hardware

AI as a Compiler: Compiling Triton kernels without the Triton compiler

arXiv:2609.36800v1 Announce Type: new Abstract: Compiler backends are expensive to build and maintain as programming models, workloads, and accelerators evolve. We investigate whether large language m

hardwarearxiv-cs-ai

An Empirical Study and Assessment of EU AI Act Compliance Checkers

arXiv:2609.36228v1 Announce Type: new Abstract: The EU AI Act introduces extensive compliance requirements for organizations that develop, deploy, or integrate AI systems. Many of these requirements a

safetyarxiv-cs-ai

ASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations

arXiv:2609.32868v2 Announce Type: replace-cross Abstract: Traditional scientific computing requires researchers to translate computational intent into environment configuration, resource requests, and

Back2Struct: Making Structured Images Editable Again

arXiv:2609.37016v1 Announce Type: new Abstract: Structured images, such as diagrams, charts, and flowcharts, are inherently symbolic and can be compactly represented in an editable format, yet in prac

safetyarxiv-cs-cv

Can Language Models Learn to Forecast Stock Prices

model-releasesarxiv-cs-cl

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,

From Neurons to Conversation: Speech Brain-Computer Interfaces

arXiv:2609.36736v1 Announce Type: cross Abstract: Speech brain-computer interfaces (BCIs) aim to restore communication by transforming neural activity related to speech, language, or communicative int

researcharxiv-cs-cl

Harness Evolution as Learning: Approximation, Generalization, and Optimization Limits of Self-Improving Personal Agents

arXiv:2609.36892v1 Announce Type: new Abstract: As the capabilities of large language models (LLMs) continue to advance, increasing attention is turning to how to translate their abilities into useful

How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs

arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of promp

applicationsarxiv-cs-ai

Tutorials

HybridCUA: Learning to Orchestrate GUI and CLI for Computer-Use Agents

arXiv:2609.38008v1 Announce Type: new Abstract: Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical use

tutorialsarxiv-cs-cv

Interactive-Policy Distillation with Bidirectional Propose-and-Verify

arXiv:2609.36546v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student model on its self-generated trajectories with dense token-level teacher feedback. However, naive OPD may

Tutorials

KernelOnet: An Interpretable Neural Operator Based on Kernel Functions

arXiv:2609.35938v1 Announce Type: new Abstract: This paper proposes an interpretable neural operator framework, the Kernel Operator Network (KernelOnet), which incorporates kernel functions explicitly

tutorialsarxiv-cs-lg

KUPAS MASTER: Distilling the Tacit Expertise of Master Practitioners into Agent-Ready Experience Corpora

arXiv:2609.37673v1 Announce Type: new Abstract: Experienced professionals know more than just facts and conclusions. They know which cues matter, why a judgment is reasonable, and which action to take

safetyarxiv-cs-ai

Matrix-game 2.0: An open-source, real-time, and streaming interactive world model

arXiv:2508.13009v5 Announce Type: replace Abstract: Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynamic

applicationsarxiv-cs-cv

MERID: Multimodal Exploration via Recursive Self-Improvement Agents for Major Depression Analysis

arXiv:2609.36235v1 Announce Type: new Abstract: Major depressive disorder (MDD) severely impacts daily activities and quality of life. Detecting MDD involves multimodal data, such as interview recordi

Multi-Class, Multi-Tier Network Intrusion Detection: A Comprehensive and Reproducible Benchmark

arXiv:2609.36039v1 Announce Type: cross Abstract: Machine learning (ML) and deep learning (DL) have dominated Intrusion Detection System (IDS) research in recent years. Unfortunately, many existing st

Neural topology optimization of ship structures under propulsion machinery vibrations

arXiv:2609.38089v1 Announce Type: cross Abstract: Ship structural vibrations contribute to noise, fatigue, and equipment damage, while dynamic-compliance topology optimization can produce pathological

applicationsarxiv-cs-ai

Hardware

Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices

arXiv:2609.35833v1 Announce Type: new Abstract: Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on

hardwarearxiv-cs-ai

NIDAR: NIR-Guided Intrinsic Decomposition for Scalable Scene-Agnostic LiDAR Intensity Reconstruction

arXiv:2609.36878v1 Announce Type: new Abstract: LiDAR return intensity provides complementary surface-response cues for robotic perception and state estimation, yet many simulation pipelines omit it o

researcharxiv-cs-ro

PolyOCR-Venus: Unified OCR Foundation Models for Text-Centric Visual Intelligence

arXiv:2609.37712v1 Announce Type: cross Abstract: Optical Character Recognition (OCR) is evolving from plain-text transcription toward general visual intelligence, requiring models to recognize, local

PrecogUI: Proactive GUI Agents via Pre-cognitive Simulation and Experience Retrieval

arXiv:2609.36923v1 Announce Type: new Abstract: Existing reactive Graphical User Interface (GUI) agents often fail in long-horizon, dynamic scenarios, where unexpected disturbances trigger attention-d

RoboFin3D: A Sim-to-Real Platform for Robotic Surface Finishing

arXiv:2609.37560v1 Announce Type: new Abstract: Grinding and sanding are fundamental processes in industrial robotic surface finishing. However, physical trials are expensive and consume workpieces, m

applicationsarxiv-cs-ro

ROSS: Relearning from Self-Generated Rollouts through Selective Supervision

arXiv:2609.35954v1 Announce Type: cross Abstract: Large language model post-training generates self-generated rollouts through reinforcement learning and on-policy distillation, yet this experience is

Sage: Formalization with Semantic Correction

arXiv:2609.35790v1 Announce Type: cross Abstract: While neural theorem provers have achieved impressive milestones in formal mathematics, they largely operate on the assumption that faithful Lean 4 fo

SAKI: Maximal-Coupling-Routed Teacher Supervision for On-Policy Distillation

arXiv:2609.36601v1 Announce Type: new Abstract: On-policy distillation (OPD) reduces train-test state mismatch by training a student on its own generated trajectories, but weak students may visit teac

safetyarxiv-cs-ai

Self-discovering RL in the Era of Experience: Is Learning History an Asset or a Burden?

arXiv:2609.35897v1 Announce Type: new Abstract: The pursuit of recursive self-improvement (RSI) toward general intelligence is divided between macro-level language model scaling and the interaction-dr

Serverless gossip training of LSTM failure detectors: A matched-protocol comparison with federated, local and centralized learning on NASA C-MAPSS

arXiv:2609.35792v1 Announce Type: new Abstract: Industrial predictive maintenance increasingly depends on learning from equipment spread across sites whose sensor data cannot easily be pooled. Federat

SimpleEvol: An Agent-Loop Framework for LLM-Driven Automated Heuristic Design with Minimal Human Priors

arXiv:2609.37172v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as powerful tools for automated heuristic design (AHD), enabling iterative generation and refinement of heuris