Search: “deployment”

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

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

DGX agent

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

model-releasesarxiv-cs-lg

29 Jul 2026

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

Local Ai

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

Applications

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

Local Ai

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

Applications

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

Applications

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

We ran a large-scale distillation attack on the Kimi K3 technical report by reading it in parallel at the Hugging Face Journal Club :) https…

We ran a large-scale distillation attack on the Kimi K3 technical report by reading it in parallel at the Hugging Face Journal Club :) https://youtu.be/MW8-kqd2SD8?si=jSKDogcUWbJ8N2k7 Our main takeawa

safetyclem-delangue--x

When Do Agent Loops Mistake Stagnation for Progress? Self-Evaluation Bias and Externally Grounded Verification in Long-Running Autonomous LLM Agent Loops

arXiv:2607.25152v1 Announce Type: new Abstract: Long-running autonomous agents plan, act, and judge their own completion without human intervention. When an agent grades its own work, self-evaluation

A Cyclic Adaptation-Generalization Framework with Uncertainty-Guided Self-Paced Learning for Long-Term Brain-Machine Interfaces

arXiv:2607.24031v1 Announce Type: new Abstract: Brain-Machine Interfaces (BMIs), which link the brain to external devices, hold great potential in rehabilitation, human performance augmentation, and h

A Simple, Optimal and Efficient Algorithm for Online Exp-Concave Optimization

arXiv:2512.23190v3 Announce Type: replace Abstract: Online eXp-concave Optimization (OXO) is a fundamental problem in online learning, where the goal is to minimize regret when loss functions are expo

Algorithmic Blindness in Large Language Models: A Calibration Study of Performance Prediction

arXiv:2602.21947v5 Announce Type: replace Abstract: Large language models (LLMs) demonstrate remarkable breadth of knowledge, yet their ability to reason about computational processes remains poorly u

Ambient pressure compensation and robust position control of oil-filled electric joint systems for underwater manipulators

arXiv:2607.24384v1 Announce Type: new Abstract: Electric joint systems are significant elements of an underwater manipulator for its actuation, drive, and control. Working in an underwater environment

researcharxiv-cs-cv

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data

arXiv:2603.07841v2 Announce Type: replace Abstract: Recent advances in large language models have strengthened Text2SQL systems that translate natural language questions into database queries. A persi

researcharxiv-cs-cl

Anticipatory Risk-Guided Reinforcement Learning for Safe Flight Through Dynamic Clutter

arXiv:2607.23565v1 Announce Type: cross Abstract: Safe quadrotor navigation in cluttered and dynamic environments depends not only on instantaneous geometric perception, but more critically on anticip

safetyarxiv-cs-lg

Are Prompt Optimizers Blind? Cross-Modal Visual Feedback for Automatic Prompt Optimization

arXiv:2607.24354v1 Announce Type: new Abstract: Automatic prompt optimization (APO) has been widely adopted to adapt vision-language models (VLMs) to downstream tasks without weight updates, yielding

researcharxiv-cs-ai

{au}: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision

arXiv:2607.24485v1 Announce Type: new Abstract: Learning the informative tactile representation while effectively adapting it to pretrained Vision-Language-Action (VLA) models remains challenging at b

researcharxiv-cs-ro

Auditing Alignment Controllability in LLMs via Political Axes

arXiv:2607.23519v1 Announce Type: cross Abstract: Political audits of large language models (LLMs) usually reduce each to one point on a political compass. But that resting point barely matters in dep

Bayesian Repetition Penalty: A Principled Adjacent-Conditional Framework for Reversing Attention Collapse in Autoregressive Language Models

arXiv:2607.22694v1 Announce Type: new Abstract: Attention collapse in autoregressive language models -- manifested as repetitive token loops where the model becomes trapped in self-reinforcing attract

Tutorials

BeyondFusion: Self-Aligned Latent Diffusion for Calibration-Free Infrared Super-Resolution and Infrared-Visible Fusion

arXiv:2607.24110v1 Announce Type: new Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cros

tutorialsarxiv-cs-cv

Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities

arXiv:2607.24056v1 Announce Type: cross Abstract: Network-wide traffic volume estimation typically relies on propagating measurements from fixed sensors, making performance highly dependent on sensor

researcharxiv-cs-ai

CC-AOS: Cost- and Horizon-Conditioned Amortized Backward Induction for Finite-Horizon Optimal Stopping

arXiv:2607.22774v1 Announce Type: new Abstract: Finite-horizon optimal stopping is a central problem in early time-series classification, where a system must decide at each sequence prefix whether the

Hardware

Certified Parallel-in-Time Sinkhorn for Dynamic Entropic Optimal Transport

arXiv:2607.24741v1 Announce Type: cross Abstract: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distri

hardwarearxiv-cs-lg

Closed-Loop Validation-Repair for Healthcare Interoperability: A Multi-Model Study of Schema Compliance in Clinical LLMs

arXiv:2607.24371v1 Announce Type: cross Abstract: Healthcare interoperability requires AI systems to produce structured outputs conforming to standardized schemas including ICD-10 for diagnostic codin

Code Arena now measures fullstack capabilities! View overall rankings across AI models on full-stack web development tasks: multi-step reaso…

model-releaseskimi-moonshot--x

Code Arena now measures fullstack capabilities! View overall rankings across AI models on full-stack web development tasks: multi-step reasoning, tool use, and end-to-end app generation. - Kimi K3 (Ma

Codebook Capacity Governs Perceptual Quality Across Resolutions in Hierarchical Discrete Video Compression

arXiv:2607.23366v1 Announce Type: cross Abstract: Learned video codecs based on continuous latent representations typically require resolution-specific retraining or rate-distortion (RD) recalibration

researcharxiv-cs-cv

Color Fundus Photography Analysis: Co-evolution of Data, Preprocessing, and Modeling toward Multimodal AI

arXiv:2607.23972v1 Announce Type: new Abstract: Color Fundus Photography (CFP) is a primary non-invasive imaging modality for large-scale screening of ophthalmic and systemic diseases. Existing survey

researcharxiv-cs-cv

ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control

arXiv:2607.22962v1 Announce Type: new Abstract: LLM agents that operate over many turns accumulate facts in an external memory store and reuse them as premises for downstream reasoning. A hallucinated

Context-Adaptive Inference: A Unified Statistical and Foundation-Model View

arXiv:2607.23304v1 Announce Type: cross Abstract: Modern predictive systems are expected to adapt their behavior to the specific situation they are facing. A clinical model should not treat every pati

Continual Knowledge Consolidation LORA for Domain Incremental Learning

arXiv:2510.16077v2 Announce Type: replace-cross Abstract: Domain Incremental Learning (DIL) is a sub-branch of continual learning that aims to address the never-ending arrival of new domains without c

Detect early and enforce firmly with Google Cloud's enhanced cost controls for AI spend

model-releasesgoogle-cloud-ai

Generative AI can make cloud costs difficult to predict. A single five-word prompt can run complex operations and generate significant costs. Traditional metrics like requests per second no longer hel

DeVA: Decoupled Video-Action Model with physical guidance for robot policy learning

arXiv:2607.24159v1 Announce Type: cross Abstract: Generalizable robot manipulation requires policies that can anticipate how visual scenes evolve while executing language instructions. While recent Vi

safetyarxiv-cs-cv

Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors

arXiv:2607.22935v1 Announce Type: new Abstract: Minimum-exposure constraints arise in recommendation, content curation, and regulated allocation when each provider, arm, or group must receive guarante

researcharxiv-cs-lg