Search: “deployment”

Comparing RAG and GraphRAG for Page-Level Retrieval Question Answering on a Math Textbook

arXiv:2509.16780v3 Announce Type: replace-cross Abstract: Large language models (LLMs) show promise as educational aids but often lack alignment with specific course materials. We investigate Retrieva

local-aiarxiv-cs-ai

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Context Assembly as the Controlled Variable: A Control-Theoretic View of Harness Policies for Frozen LLM Agents

DGX agent

arXiv:2607.25408v1 Announce Type: new Abstract: A growing body of 2026 work applies control theory to LLM agents: Lyapunov-certified stability for tool-mediated controllers (Prinos et al., 'Stable Age

safetyarxiv-cs-ai

29 Jul 2026

Contextual Deconvolution for Variance-Stable Demand Sensing: Kernel-Modulated Operators in Promotional Retail

arXiv:2607.25664v1 Announce Type: new Abstract: Machine learning demand forecasts optimize statistical accuracy yet leave excess operational volatility that inflates safety stock and amplifies the Bul

safetyarxiv-cs-lg

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models

arXiv:2607.25918v1 Announce Type: new Abstract: World-Action Models (WAMs) augment robot policies with future visual prediction, but it remains unclear what the visual modality should learn for contro

local-aiarxiv-cs-ro

Decision-Level Hijacking: Injecting Cognitive Bias into Large Language Models via Bit-Flip Attacks

arXiv:2607.25227v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly

Agents

Distributing Security Controls Through Harness Engineering

arXiv:2607.25890v1 Announce Type: new Abstract: AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizatio

agentsarxiv-cs-ai

Does Runtime Topology Context Improve LLM-Generated Kubernetes Security Patches?

arXiv:2607.25995v1 Announce Type: cross Abstract: Kubernetes is central to the cloud-native ecosystem, orchestrating containerised workloads. Recent work suggests that large language models (LLMs) can

Egocentric Station Holding of Robotic Fish in Unknown Turbulent Background Flow

arXiv:2607.24860v1 Announce Type: new Abstract: Approaching a target position and holding station in flowing water is a fundamental and critical capability for robotic fish operating in natural aquati

safetyarxiv-cs-ro

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

arXiv:2607.26000v1 Announce Type: cross Abstract: Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to en

applicationsarxiv-cs-ai

Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners

arXiv:2607.25532v1 Announce Type: new Abstract: Consider a model trained at a single hospital to predict patient recovery, where the measured feature X bundles the patient's true health signal (C) wit

Every Time I Hire a Linguist, Inference Costs Go Down: On Linguistic Rules as Effective Prompt Compressors

arXiv:2607.25335v1 Announce Type: cross Abstract: Prompt compression shortens LLM input to reduce inference cost, yet existing methods score token importance through LM forward passes. It remains ques

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening

arXiv:2507.11548v3 Announce Type: replace-cross Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias re

FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model

arXiv:2607.25791v1 Announce Type: new Abstract: Falls represent a critical public health challenge, and accurate detection of the impact moment when an individual hits the ground is crucial for timely

researcharxiv-cs-cv

FlashEvaluator: Expanding Search Space with Parallel Sequence-Level Evaluation

arXiv:2603.02565v2 Announce Type: replace-cross Abstract: The Generator-Evaluator (G-E) framework generates K candidate sequences and uses an evaluator to select the highest-scoring one, which is wide

local-aiarxiv-cs-cl

From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations

arXiv:2607.25687v1 Announce Type: cross Abstract: Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the c

GeoMFD: Continual Drone-View Geo-Localization with Geometry-Aware Adapter and Margin-Field Distillation

arXiv:2607.25788v1 Announce Type: new Abstract: Existing drone-view geo-localization (DVGL) methods are mainly developed under a static training paradigm, where models are optimized for fixed environm

local-aiarxiv-cs-cv

How Small Can You Go? A Controlled Study of LoRA Rank, Target Modules, and Quantization Trade-offs for Text-to-SQL on a 60M-Parameter Model

arXiv:2607.25583v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) and low-bit quantization are now standard tools for adapting language models under tight compute budgets, yet the

Input-Aware Dynamic Backdoor Attack Against Quantum Neural Networks

arXiv:2607.11843v2 Announce Type: replace-cross Abstract: Quantum Neural Networks (QNNs) are a promising framework for quantum machine learning on near-term quantum devices, but their security risks r

researcharxiv-cs-lg

Inspect India Evals: An Open Benchmarking Framework for Evaluating Large Language Models in the Indian Linguistic and Cultural Context

arXiv:2607.25375v1 Announce Type: new Abstract: India is a vast nation of over 1.4 billion people, varied by hundreds of diverse and locally specific traditions and cultures and 22 officially recogniz

Joint Text-Audio Alignment for EEG-to-Text Decoding in Chinese Speech Production and Perception

arXiv:2607.25626v1 Announce Type: new Abstract: Decoding speech information directly from scalp electroencephalography (EEG) into text provides a potential non-invasive neural communication pathway fo

Long-Term PM2.5 Forecasting Using a DTW-Enhanced CNN-GRU Model

arXiv:2510.22863v2 Announce Type: replace-cross Abstract: Reliable long-term forecasting of PM2.5 concentrations is critical for public health early-warning systems, yet existing deep learning approac

Memory Layer: Train the In-Model Cache for Recommendation Models

arXiv:2607.25110v1 Announce Type: cross Abstract: Early ranking stages in recommendation systems precompute item embeddings and cache them in-model for scoring within strict latency constraints. Becau

applicationsarxiv-cs-lg

Modular Robotic Catheters for Endovascular Aneurysm Repair

arXiv:2607.25807v1 Announce Type: new Abstract: Fenestrated/Branched endovascular aneurysm repair (FEVAR/BEVAR) require surgeons to navigate catheters and guidewires into various branches of the abdom

researcharxiv-cs-ro

NEXT: Reasoning-Driven Video Recommendation via a Vision-Language Model

arXiv:2607.24789v1 Announce Type: cross Abstract: We present NEXT (Next-interest EXploration Transformer), a reasoning-driven video recommendation framework that reasons over the video a user has just

safetyarxiv-cs-cv

OmniQEC: discovering practical quantum error-correcting codes by an AI scientist

arXiv:2607.25865v1 Announce Type: cross Abstract: Quantum error correction (QEC) is indispensable for scalable fault-tolerant quantum computing. However, discovering QEC codes that remain effective is

On benchmarking long-context agentic instruction following. Agent benchmarks mostly reward reaching the answer. This new benchmark measures …

On benchmarking long-context agentic instruction following. Agent benchmarks mostly reward reaching the answer. This new benchmark measures whether the agent reached it the permitted way, which is the

model-releasesdair-ai--x

OpenPVMapper: A Multi-source, Nationwide Database of Rooftop Photovoltaic Systems in France

model-releasesarxiv-cs-cv

arXiv:2607.25153v1 Announce Type: new Abstract: Rooftop photovoltaic (PV) systems account for the vast majority of PV grid connections, yet no open, comprehensive, installation-level dataset of these

PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing

arXiv:2603.26136v3 Announce Type: replace Abstract: Message Passing Neural Networks (MPNNs) have achieved strong performance on tasks involving relational data. However, small perturbations to graph s

Penelope: Localized Latent Recurrence for Efficient Structured Reasoning

arXiv:2607.25915v1 Announce Type: new Abstract: Complex structured reasoning tasks often require additional computation, yet current language models obtain it mainly by increasing parameter scale or b

Pictura: Perspective-View Self-Play at Scale for Driving

arXiv:2607.26005v1 Announce Type: cross Abstract: Self-play in simulation produces robust driving policies at scale. Demonstrations of such behavior have been made using privileged vectorized observat

Tutorials

PILA: Plug-and-Play Insertion for LLM-native Advertising

arXiv:2607.25590v1 Announce Type: new Abstract: How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recen

tutorialsarxiv-cs-cl

PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning

arXiv:2508.00344v5 Announce Type: replace Abstract: Large Language Models (LLMs) have shown remarkable advancements in tackling agent-oriented tasks. Despite their potential, existing work faces chall

Hardware

Quasi-SVD: Learning a Lie-constrained matrix factorisation for real-time imaging

arXiv:2607.25967v1 Announce Type: new Abstract: Singular Value Decomposition (SVD) underlies matrix factorisation tasks across computational imaging, with medical applications increasingly demanding r

hardwarearxiv-cs-cv

RDQ: Residual Distribution Quantization for Large Language Models

arXiv:2607.10137v2 Announce Type: replace Abstract: Post-training quantization (PTQ) of large language models degrades sharply below 4-bit precision. We identify the root cause as residual stream dist

Robust Unsupervised Network Intrusion Detection via Federated Learning with Selective Aggregation under Anomalous Sample Contamination

arXiv:2607.25439v1 Announce Type: cross Abstract: Network intrusion detection systems (NIDS) have become essential for Internet of Things (IoT) environments, as malware targeting IoT devices continues

local-aiarxiv-cs-lg

SAGE: Stochastic Prompt Optimization via Agent-Guided Exploration

arXiv:2606.18902v2 Announce Type: replace Abstract: Context engineering has emerged as a primary lever for improving AI systems without parameter updates. Recent work showing that textual gradients do

SPARC Segmentation to Prediction via Affine Regression and Counterfactuals

arXiv:2607.25413v1 Announce Type: new Abstract: Transaction propensity prediction in B2B e commerce presents unique challenges distinct from B2C contexts, primarily due to the heterogeneous procuremen

applicationsarxiv-cs-lg

Agents

Speculate While You Reason: Teaching Agents to Predict Their Next Tool Call via Joint Agent-Speculator RL

arXiv:2607.25816v1 Announce Type: new Abstract: Large language model agents often spend substantial wall-clock time waiting for tool call results. Tool-call speculation can hide this latency by predic

agentsarxiv-cs-ai

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies

arXiv:2607.25716v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving training of automatic speech recognition (ASR) systems across distributed data sources, yet its appli

TaylorPODA: A Taylor Expansion-Based Method to Improve Post-Hoc Attributions for Opaque Models

arXiv:2507.10643v4 Announce Type: replace-cross Abstract: Post-hoc model-agnostic local attribution (LA) methods have been widely adopted to explain opaque AI models by quantifying feature-wise contri

local-aiarxiv-cs-ai

Time-Frequency Consistency Learning for Robust Speech Deepfake Detection

arXiv:2607.17761v2 Announce Type: replace-cross Abstract: Recently, speech deepfake detection (SDD) has achieved significant progress. However, its robustness evaluation remains largely confined to co

Tokens are All You Need: Dual-purpose Semantic IDs for Achieving LLM-Level I/O Efficiency in recommendation systems

arXiv:2607.24865v1 Announce Type: cross Abstract: Large-scale recommendation systems face 'Memory Wall' bottlenecks due to massive, dense embedding tables. While generative retrieval uses discrete tok

applicationsarxiv-cs-ai

Agents

Towards an Agent Operating System - Lessons from Classical and Cloud OS

arXiv:2607.25076v1 Announce Type: new Abstract: Every major wave of platform software follows the same arc: an initial period of experimentation with competing frameworks and ad-hoc implementations, f

agentsarxiv-cs-ai

Towards Understanding the Cognitive Habits of Large Reasoning Models

arXiv:2506.21571v3 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs), which autonomously produce a reasoning Chain of Thought (CoT) before producing final responses, offer a promisi

Tri-Manual Visuomotor Imitation Learning of Robot Policies

arXiv:2607.25731v1 Announce Type: new Abstract: Bimanual teleoperation provides an effective way to collect robot demonstrations, but it assumes that the operator and robot have matching numbers of si

safetyarxiv-cs-ro

TWICE: Two-Clock, Two-Window Learning for Long-Horizon Conversion Prediction in Online Advertising

arXiv:2607.25404v1 Announce Type: new Abstract: Long-horizon conversion prediction under delayed feedback creates a two-clock, two-window learning problem in online advertising. A short base observati

Two of the people most responsible for scaling the transformer are now betting on a next act. @MillionInt ran the Reasoning 🍓 team at OpenA…

model-releasessonya-huang--x

Two of the people most responsible for scaling the transformer are now betting on a next act. @MillionInt ran the Reasoning 🍓 team at OpenAI. @_arohan_ was a pre-training lead on Gemini after years at

We hope these experiments serve as a reminder that evals rarely measure models in isolation—they also measure a bundle of less visible choic…

We hope these experiments serve as a reminder that evals rarely measure models in isolation—they also measure a bundle of less visible choices about API settings, harness design, and prompting. If you

applicationsopenai--x