Search: “inference”

arXiv:2606.10660v1 Announce Type: cross Abstract: AI inference services -- API subscriptions, enterprise chat tools, and SaaS products with embedded AI features -- fall unambiguously within Scope 3 Ca

arXiv:2606.09874v1 Announce Type: new Abstract: Reconstruction-based methods are widely used for time series anomaly detection, where models are trained to reconstruct subsequences, and anomalies are

arXiv:2606.10008v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) provide a naturally temporal machine-learning framework. Their neurons maintain an internal state and propagate informa

arXiv:2606.07665v1 Announce Type: cross Abstract: Transformer inference increasingly depends on specialized compiler and runtime support, but real model graphs still require semantic decisions about w

arXiv:2606.08129v1 Announce Type: new Abstract: Large language models (LLMs) differ in architecture, training data, and optimization procedures, yet they may still develop similar internal inference p

arXiv:2606.07677v1 Announce Type: cross Abstract: Electronic health records (EHR) pose large-scale multi-disease modeling problems in which many outcomes are rare and strongly influenced by shared ris

arXiv:2606.09551v1 Announce Type: cross Abstract: Two-server secure inference allows a client to query a hosted large language model (LLM) without revealing prompts or embeddings. Recent GPU systems b

arXiv:2509.24762v3 Announce Type: replace Abstract: Modeling event sequences of multiple event types with marked temporal point processes (MTPPs) provides a principled way to uncover governing dynamic

arXiv:2603.23640v2 Announce Type: replace-cross Abstract: Deploying large language models on-device for always-on personal agents demands sustained inference from hardware tightly constrained in power

arXiv:2606.07141v1 Announce Type: cross Abstract: Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owne

arXiv:2509.23385v5 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) is transforming experimental sciences by enabling parameter estimation in complex non-linear models from simu

arXiv:2606.04778v1 Announce Type: new Abstract: Safety-aligned Large Language Models (LLMs) remain vulnerable to interventions during inference that redirect generation toward harmful outputs. Recent

arXiv:2606.05004v1 Announce Type: cross Abstract: With the widespread deployment of public large language models (LLMs) such as ChatGPT, protecting user prompt privacy has become an increasingly criti

A Together AI representative announced a talk scheduled for Sunday, June 7th at AGI House focusing on DeepSeek V4 and inference optimization on Together Compute's platform. The event was promoted as a

arXiv:2606.03910v1 Announce Type: cross Abstract: Disaggregated LLM inference forces the KV cache to traverse the datacenter network before decoding begins, so transfer time enters directly into the T

DigitalOcean discusses infrastructure and platform capabilities designed to support the inference phase of machine learning, where trained models are deployed to make predictions on new data at scale.

arXiv:2606.02823v1 Announce Type: new Abstract: Two-bit weight quantization is attractive for memory-efficient LLM inference, but the standard W2 level set {-2,-1,0,+1} often collapses under aggressiv

arXiv:2606.03736v1 Announce Type: cross Abstract: Resource-constrained pricing controllers can make fixed-price inference impossible: the controller's resource state may remove the target price neighb

arXiv:2606.00913v1 Announce Type: cross Abstract: Multi-arm bandit algorithms are increasingly used in online platforms, clinical trials, and social science experiments, but valid statistical inferenc

arXiv:2606.01007v1 Announce Type: cross Abstract: Sparsely activated Mixture-of-Experts (MoE) models scale capacity via conditional computation, but distributed inference suffers from cross-GPU expert

arXiv:2606.00279v1 Announce Type: cross Abstract: Verifying claims about AI workloads is a pre- requisite for credible AI governance of covert adversaries (who comply with monitoring only when detecti

arXiv:2606.01413v1 Announce Type: cross Abstract: It is crucial for modern on-device AI systems that rely on retrieval-augmented inference to release and share datastores without compromising individu

arXiv:2606.02562v1 Announce Type: cross Abstract: Autonomous robots that interact with people must make safe and efficient decisions under human-induced uncertainty, such as their preferences, goals,

Perplexity discusses hybrid agentic inference in Perplexity Computer, which likely describes a computational approach that combines processing between local machines and data centers. The concept sugg

arXiv:2606.00966v1 Announce Type: new Abstract: Vision-Language Action (VLA) models continue to face challenges such as slow inference speed and difficulty performing fine-grained motion adjustments,

arXiv:2602.02819v3 Announce Type: replace Abstract: Membership Inference Attacks (MIAs) aim to distinguish training points (members) from unseen data (non-members), and are widely used to quantify mem

DigitalOcean's serverless inference offering enables developers to deploy and run machine learning models without managing underlying infrastructure, automatically scaling resources based on demand. T

arXiv:2605.30089v1 Announce Type: new Abstract: Standard Set Representation Learning methods typically excel on curated data but often overlook the challenge of inference-time element corruption. This

arXiv:2605.30292v1 Announce Type: cross Abstract: Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable, and predictor

This article discusses security measures and best practices for protecting AI model inference endpoints from unauthorized access and theft, likely covering topics such as API authentication, rate limi

arXiv:2505.19342v2 Announce Type: replace-cross Abstract: Multi-device inference can reduce Transformer latency by parallelizing computation. However, existing methods require high inter-device bandwi

arXiv:2605.27991v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have achieved remarkable empirical success, yet their training dynamics remain understood mainly from optimization rather

arXiv:2605.27499v1 Announce Type: new Abstract: Flow and diffusion generative models have established themselves as widely adopted density estimators for simulation-based inference (SBI), extending na

arXiv:2605.28760v1 Announce Type: new Abstract: Zeroth-order (ZO) fine-tuning is attractive for large language models because it replaces backpropagation with forward objective evaluations. Existing i

arXiv:2605.27825v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) test whether a target data record belongs to a system's private data, and have become a standard tool to measure p

OpenCode now integrates with DigitalOcean's Inference Router, enabling intelligent routing of AI model requests across distributed infrastructure. This integration allows developers to optimize model

arXiv:2605.27526v1 Announce Type: cross Abstract: We develop semiparametrically efficient inference for kernel measures of noise heterogeneity in additive noise models. In many applications, the regre

arXiv:2605.27474v1 Announce Type: cross Abstract: Estimating how an outcome responds to a continuous treatment (the Average Dose-Response Function, or ADRF) is a core causal-inference primitive. Howev

arXiv:2605.27740v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the linear growth of the self-attention key-value (KV) cache. Top-k sparse att

arXiv:2605.28087v1 Announce Type: new Abstract: Service robots must infer object ownership to correctly interpret instructions such as 'bring me my cup.' However, ownership is a latent attribute that

arXiv:2605.26289v1 Announce Type: new Abstract: Multi-agent tool calling is becoming the dominant interaction pattern for LLM-based systems, yet existing inference frameworks treat each tool call as a

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

arXiv:2503.07482v2 Announce Type: replace-cross Abstract: Membership Inference Attacks (MIAs) aim to estimate whether a specific data point was used in the training of a given model. Existing state-of

arXiv:2605.24528v1 Announce Type: new Abstract: Real world decision-making requires constructing mental models under uncertainty over evidence, over the underlying causal rules, and over the state of

Artificial intelligence inference routing startup OpenRouter Inc. today announced it raised 113 million in new funding led by CapitalG, Alphabet Inc.’s independent growth fund, to push the envelope fo

This post describes implementing DCGAN (Deep Convolutional Generative Adversarial Network) inference on resource-constrained microcontroller hardware, achieving image generation with a 12.6 million pa