Search: “models”

Reliability-Asymmetric Spacecraft Autonomy: Co-Designing a Capable Learned GNC Stack with a Verified, Adaptation-Aware Runtime Shield

arXiv:2606.25366v1 Announce Type: new Abstract: Deep-space missions need onboard autonomy that is both capable and certifiable. Rule-based autonomy is certifiable but brittle, while learned autonomy i

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Run Codex in the cloud – DigitalOcean for Codex is now available

DGX agent

DigitalOcean has launched a cloud-based service enabling users to run OpenAI's Codex, an AI code generation model, on DigitalOcean's infrastructure. This offering allows developers to access Codex cap

industrydigitalocean

25 Jun 2026

Scalable Peptide Design via Memory-Efficient Equivariant Transformer

arXiv:2606.25006v1 Announce Type: new Abstract: Target-specific peptide design requires sequence and structure co-design under full atom geometric constraints. Latent generative frameworks offer an ef

Hardware

Scaling AI Inference Across Multiple GPUs Using NVIDIA TensorRT with Multi-Device Inference Support

NVIDIA TensorRT's multi-device inference feature scales inference across multiple GPUs, enabling deployment of models that exceed single-GPU memory or reducing latency for memory-bound workloads. Each

hardwarenvidia-developer

Securing Time Integrity in Energy IoT Against Clock Drift and Y2K38 Failures

arXiv:2601.23147v2 Announce Type: replace Abstract: The integrity of time in distributed Internet of Things (IoT) devices is crucial for reliable operation in energy cyber-physical systems, such as sm

Shift Variant Image Degradation and Restoration Using Singular Value Decomposition

arXiv:2606.25818v1 Announce Type: new Abstract: Shift-variant image degradation is frequently encountered in practical imaging systems where the point spread function (PSF) varies across the image fie

Simplify to Amplify: Achieving Information-Theoretic Bounds with Fewer Steps in Spectral Community Detection

arXiv:2602.17104v2 Announce Type: replace-cross Abstract: We propose a streamlined spectral algorithm for community detection in the two-community stochastic block model (SBM) under constant edge dens

Teach-to-Reason: Competition-Guided Reasoning with a Self-Improving Teacher

arXiv:2606.25407v1 Announce Type: new Abstract: Chest X-ray visual question answering (CXR VQA) requires models not only to predict correct answers, but also to produce reliable medical reasoning. How

The cognitive, affective, and behavioral expression of self-stigma among people who use drugs in online substance use communities

arXiv:2606.25143v1 Announce Type: new Abstract: Objectives: To develop a codebook for self-stigma across cognitive, affective, and behavioral domains, and to estimate the prevalence, co-occurrence, an

researcharxiv-cs-cl

The Inference-Compute Frontier and a Latency-Efficient Architecture for Limit Order Book Prediction

arXiv:2606.25986v1 Announce Type: new Abstract: We study whether a scaling-law-style inference-compute frontier appears in limit order book prediction. Using FI-2010 and a suite of models ranging from

TIDAL: Temporally Interleaved Diffusion and Action Loop for High-Frequency VLA Control

arXiv:2601.14945v2 Announce Type: replace Abstract: Large-scale Vision-Language-Action (VLA) models offer semantic generalization but suffer from high inference latency, limiting them to low-frequency

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TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems

arXiv:2606.25627v1 Announce Type: new Abstract: Distributed intelligent systems increasingly need to train across data silos without centralizing raw data. Federated learning keeps data local but can

local-aiarxiv-cs-lg

TRUSTMEM: Learning Trustworthy Memory Consolidation for LLM Agents with Long-Term Memory

arXiv:2606.25161v1 Announce Type: new Abstract: Large language model (LLM) agents rely on long-term memory to support extended interactions and personalized assistance beyond finite context windows. E

researcharxiv-cs-ai

TTSA3R: Training-Free Temporal-Spatial Adaptive Persistent State for Streaming 3D Reconstruction

arXiv:2601.22615v3 Announce Type: replace Abstract: Streaming recurrent models enable efficient 3D reconstruction by maintaining persistent state representations. However, they suffer from catastrophi

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Understanding the brain with AI-driven explanations and experiments

researchmicrosoft-research

Researchers introduce generative causal testing, which translates black box models into clear hypotheses and verifies them in the scanner, revealing what specific brain regions respond to in language.

A Comparative Study of Bayesian Contextual Bandits for Real-Time Warehouse Sorter Optimization

arXiv:2606.23977v1 Announce Type: new Abstract: Efficient sorter diversion control of automated material handling systems (MHS) is critical for optimizing operational efficiency in large-scale warehou

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Agon: An Autonomous Large-Scale Omnidisciplinary Research System Built on Prompt Economy

arXiv:2606.24177v1 Announce Type: cross Abstract: Large language models are making research production scalable, shifting the bottleneck from producing artifacts to judging claims. We present extsc{Ag

agentsarxiv-cs-ai

AI is quickly moving beyond emulating the human mind to predicting an increasingly large percentage of all observations in the world. Genera…

industrycristobal-valenzuela--x

AI is quickly moving beyond emulating the human mind to predicting an increasingly large percentage of all observations in the world. General world models will become a new foundational infrastructure

Aligning Audio Captions with Human Preferences

arXiv:2509.14659v3 Announce Type: replace-cross Abstract: Current audio captioning relies on supervised learning with paired audio-caption data, which is costly to curate and may not reflect human pre

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all sports should open their data via MCP so everyone can easily build visualizations this shows the global nature of groups + current statu…

Yohei Nakajima proposes that sports organizations should make their data openly accessible through Model Context Protocol (MCP) to enable broader public creation of visualizations and data analyses. T

agentsyohei-nakajima--x

An Introduction to Causal Reinforcement Learning

arXiv:2606.24160v1 Announce Type: new Abstract: Causal inference provides a set of principles and tools that allow one to combine data and knowledge about an environment to reason with questions of co

ARIA: Adaptive Region-Based Importance Allocation for Conditional Diffusion Distillation

arXiv:2606.23898v1 Announce Type: cross Abstract: Distilling conditional diffusion models aims to transfer the behavior of a large teacher to a smaller student while preserving alignment across condit

b9784

local-aillama-cpp-releases

Build b9784 is a release of llama.cpp, a C/C++ project that enables large language model inference with minimal setup on a wide range of hardware. The release includes pre-compiled binaries for multip

Breaking Shortcut Learning for Cross-Trial EEG-Guided Target Speech Extraction via Two-Stage Training

arXiv:2606.24164v1 Announce Type: cross Abstract: Recent end-to-end models for EEG-guided target speech extraction report impressive results, underscoring potential for neuro-steered hearing technolog

COMPANY BUILT ON IP THEFT RAGES AGAINST THEFT OF ITS OWN IP

COMPANY BUILT ON IP THEFT RAGES AGAINST THEFT OF ITS OWN IP ANTHROPIC ACCUSED ALIBABA OF UNAUTHORIZED ACCESS TO ITS AI MODELS, OUTLINING ITS ALLEGATIONS IN LETTERS SENT TO U.S. SENATORS AND THE WHITE

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CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference

arXiv:2606.24467v1 Announce Type: new Abstract: Long-context large language model (LLM) inference is increasingly constrained by the memory footprint and decoding cost of key-value (KV) caches, limiti

researcharxiv-cs-ai

Cross-Dataset, Age, and Gender Generalization: A Comprehensive Analysis of Fine-Tuning Strategies for Low-Resource Children's ASR

arXiv:2606.19791v2 Announce Type: replace-cross Abstract: The challenge associated with recognizing dysarthric speech primarily arises from pronounced acoustic variability attributed to impaired artic

researcharxiv-cs-ai

Cross-Lingual Exploration for Parametric Knowledge

arXiv:2606.24579v1 Announce Type: new Abstract: Parametric knowledge in Large Language Models is not equally accessible across languages. As a result, standard inference techniques often struggle to s

local-aiarxiv-cs-cl

Data Augmentation: A Fourier Analysis Perspective

arXiv:2606.24418v1 Announce Type: new Abstract: Data augmentation is a simple and model-agnostic approach for exploiting known invariances in learning problems. Given a group acting on the input space

Deep numerical schemes for systems of Ergodic BSDEs with applications to regime-switching forward utilities

arXiv:2606.24271v1 Announce Type: cross Abstract: In this paper, we introduce two neural-network-based numerical schemes for solving systems of coupled ergodic Backward Stochastic Differential Equatio

local-aiarxiv-cs-lg

DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation

arXiv:2606.23950v1 Announce Type: new Abstract: Subject-driven image generation faces an 'Identity-Diversity Paradox', where strong identity preservation often leads to rigid and low-diversity outputs

Elon Musk denies Tesla’s Autopilot caused crash that killed grandmother

A Tesla Model 3 crashed into a residential home in Katy, Texas, killing a 76-year-old grandmother, with the driver claiming Autopilot was active at the time. Elon Musk disputed the claim, and Tesla's

industryars-technica

EnerInfer: Energy-Aware On-Device LLM Inference

arXiv:2606.23001v1 Announce Type: cross Abstract: On-device LLM inference is increasingly attractive for privacy-preserving, reliable, and cost-effective deployment, yet its energy and thermal costs r

local-aiarxiv-cs-lg

Escaping the Self-Confirmation Trap: An Execute-Distill-Verify Paradigm for Agentic Experience Learning

arXiv:2606.24428v1 Announce Type: new Abstract: Experience-driven self-evolution is critical for large language model (LLM) agents to improve through open-world interaction. However, existing experien

safetyarxiv-cs-cl

Evaluating the Interpretability of Sparse Autoencoders with Concept Annotations

arXiv:2606.24716v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are increasingly used to extract interpretable concepts from vision and vision language models, yet existing evaluation met

EvidenceLens: A Claim-Evidence Matrix for Auditing Financial Question Answering

arXiv:2606.23724v1 Announce Type: cross Abstract: Large language models are increasingly used to answer questions over annual reports, earnings decks, and analyst notes, yet their outputs remain diffi

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From Task-Guided Conversational Graphs to Goal-Oriented Dialogue Runtimes

arXiv:2606.23797v1 Announce Type: cross Abstract: Graph and multi-agent orchestration frameworks make production large language model (LLM) workflows practical, but they do not by themselves solve con

agentsarxiv-cs-ai

Google starts lowering Play Store fees, making good on Epic Games settlement

Google announced changes to its Play Store model to settle its years-long legal fight with Epic Games, including lowering the commission fee to 20 percent on in-app purchases and creating a new progra

industryars-technica

Information-Theoretic Classifier-Free Guidance with Adaptive Schedule Optimization

arXiv:2606.24025v1 Announce Type: new Abstract: Diffusion models have achieved strong performance in image, text-to-image, and video generation, where conditional generation is often controlled by cla

InSight: Self-Guided Skill Acquisition via Steerable VLAs

arXiv:2606.24884v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can learn manipulation skills from demonstrations, but their capabilities are bounded by the skills in the trainin

agentsarxiv-cs-ai

Tutorials

IV-CoT: Implicit Visual Chain-of-Thought for Structure-Aware Text-to-Image Generation

arXiv:2606.24849v1 Announce Type: cross Abstract: Unified multi-modal large language models (MLLMs) have achieved strong text-to-image generation quality, but still struggle with structure-aware promp

tutorialsarxiv-cs-ai

Latent Visual States for Efficient Multimodal Reasoning

arXiv:2606.24233v1 Announce Type: new Abstract: The integration of visual evidence has significantly enhanced the capabilities of large multimodal models. However, this integration predominantly relie

safetyarxiv-cs-cv

Machine Learning Classification and Portfolio Construction: Does the Loss Function Matter?

arXiv:2108.02283v3 Announce Type: replace-cross Abstract: Classification outperforms regression across matched machine learning models in portfolio construction. A stacking ensemble of gradient booste

ModTGCN: Modularity-aware Graph Neural Networks for Text Classification

arXiv:2606.23694v1 Announce Type: new Abstract: Graph-based text classification models typically rely on local neighborhood aggregation and overlook global community structure, despite semantic docume

researcharxiv-cs-cl

MorVess: Morphology-Aware Pulmonary Vessel Segmentation Network

arXiv:2606.24214v1 Announce Type: new Abstract: Accurate pulmonary vessel segmentation remains challenging due to the sparse, tortuous, and multi-scale nature of vascular structures, where small branc

Tutorials

MVG-KAN: Multi-View Geo-Wind Guided KAN for PM_{2.5} Forecasting

arXiv:2606.24347v1 Announce Type: new Abstract: Accurate short-term PM_{2.5} forecasting is important for public health protection, air-quality early warning, and urban environmental management. Howev

tutorialsarxiv-cs-ai

Hardware

OpenAI, Broadcom debut custom Jalapeño chip for AI inference

OpenAI Group PBC today revealed a custom chip called Jalapeño that it will use to power its large language models. The processor is the fruit of a collaboration with Broadcom Inc., which is no strange

hardwaresiliconangle

OpenAI reveals its first AI processor: Jalapeño

OpenAI has just revealed a new 'intelligence processor' chip for AI servers made in partnership with Broadcom. The chip, called Jalapeño, is designed to power current and future large language models,

industrythe-verge-ai