Search: “inference”

Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference

arXiv:2511.21223v2 Announce Type: replace-cross Abstract: Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models. However, its formul

21 May 2026

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Model Releases

CoX-MoE: Coalesced Expert Execution for High-Throughput MoE Inference with AMX-Enabled CPU-GPU Co-Execution

DGX agent

arXiv:2605.17889v1 Announce Type: new Abstract: The Mixture-of-Experts (MoE) architecture improves computational efficiency via sparse expert activation, but throughput-oriented inference faces substa

model-releasesarxiv-cs-lg

19 May 2026

Accelerating Particle-based Energetic Variational Inference

arXiv:2504.03158v2 Announce Type: replace-cross Abstract: In this work, we propose a new particle-based variational inference (ParVI) method for accelerating the Energetic Variational Inference with I

14 May 2026

Applications

Realtime-VLA FLASH: Speculative Inference Framework for Diffusion-based VLAs

arXiv:2605.13778v1 Announce Type: cross Abstract: Diffusion-based vision-language-action models (dVLAs) are promising for embodied intelligence but are fundamentally limited in real-time deployment by

applicationsarxiv-cs-cv

14 May 2026

Enabling Performant and Flexible Model-Internal Observability for LLM Inference

arXiv:2605.11093v1 Announce Type: new Abstract: Today's inference-time workloads increasingly depend on timely access to a model's internal states. We present DMI-Lib, a high-speed deep model inspecto

safetyarxiv-cs-lg

FIS-DiT: Breaking the Few-Step Video Inference Barrier via Training-Free Frame Interleaved Sparsity

arXiv:2605.11869v1 Announce Type: new Abstract: While the overall inference latency of Video Diffusion Transformers (DiTs) can be substantially reduced through model distillation, per-step inference l

researcharxiv-cs-cv

Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference

model-releasesarxiv-cs-cl

arXiv:2505.13770v3 Announce Type: replace-cross Abstract: Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it rema

Learning U-Statistics with Active Inference

arXiv:2605.11638v1 Announce Type: cross Abstract: U-statistics play a central role in statistical inference. In many modern applications, however, acquiring the labels required for U-statistics is cos

Combining Mechanical and Agentic Specification Inference for Move

model-releasesarxiv-cs-ai

arXiv:2605.10005v1 Announce Type: cross Abstract: In this paper, we describe early work on a specification inference tool for the Move Prover that combines a weakest-precondition (WP) analysis over Mo

ConfoundingSHAP: Quantifying confounding strength in causal inference

arXiv:2605.10533v1 Announce Type: new Abstract: In causal inference, confounders are variables that influence both treatment decisions and outcomes. However, unlike as in randomized clinical trials, t

GELATO: Generative Entropy- and Lyapunov-based Adaptive Token Offloading for Device-Edge Speculative LLM Inference

arXiv:2605.10124v1 Announce Type: cross Abstract: The recent growth of on-device Large Language Model (LLM) inference has driven significant interest in device-edge collaborative LLM inference. As a p

local-aiarxiv-cs-lg

Split CNN Inference on Networked Microcontrollers

arXiv:2605.09357v1 Announce Type: cross Abstract: Running deep neural networks on microcontroller units (MCUs) is severely constrained by limited memory resources. While TinyML techniques reduce model

Understanding Asynchronous Inference Methods for Vision-Language-Action Models

model-releasesarxiv-cs-ai

arXiv:2605.08168v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models offer a promising path to generalist robot control, but their inference latency causes observation staleness when

Hardware

LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites

arXiv:2605.05615v2 Announce Type: replace Abstract: Large language models (LLMs) impose rapidly growing energy demands, creating an emerging energy and carbon crisis driven by large-scale inference. S

hardwarearxiv-cs-lg

11 May 2026

Relay Buffer Independent Communication over Pooled HBM for Efficient MoE Inference on Ascend

arXiv:2605.06055v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) inference requires large-scale token exchange across devices, making dispatch and combine major bottlenecks in both p

11 May 2026

StreamPhy: Streaming Inference of High-Dimensional Physical Dynamics via State Space Models

arXiv:2605.07384v1 Announce Type: new Abstract: Inferring the evolution of high-dimensional and multi-modal (e.g., spatio-temporal) physical fields from irregular sparse measurements in real time is a

11 May 2026

Hardware

A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints

arXiv:2605.04595v1 Announce Type: new Abstract: The rapid adoption of large language models (LLMs) has created significant challenges for efficient inference at scale. Unlike traditional workloads, LL

hardwarearxiv-cs-lg

7 May 2026

When Does Gene Regulatory Network Inference Break? A Controlled Diagnostic Study of Causal and Correlational Methods on Single-Cell Data

arXiv:2605.04930v1 Announce Type: new Abstract: Despite theoretical advantages, causal methods for Gene Regulatory Network (GRN) inference from single-cell RNA-seq data consistently fail to match or o

7 May 2026

Amortized Variational Inference for Joint Posterior and Predictive Distributions in Bayesian Uncertainty Quantification

arXiv:2605.03710v1 Announce Type: cross Abstract: Bayesian predictive inference propagates parameter uncertainty to quantities of interest through the posterior-predictive distribution. In practice, t

6 May 2026

A PAC-Bayesian Analysis of Channel-Induced Degradation in Edge Inference

arXiv:2601.10915v2 Announce Type: replace-cross Abstract: In the emerging paradigm of edge learning, neural networks (NNs) are partitioned across distributed edge devices that collaboratively perform

5 May 2026

Agents

Agentic Compilation: Mitigating the LLM Rerun Crisis for Minimized-Inference-Cost Web Automation

arXiv:2604.09718v2 Announce Type: cross Abstract: LLM-driven web agents operating through continuous inference loops -- repeatedly querying a model to evaluate browser state and select actions -- exhi

agentsarxiv-cs-ai

1 May 2026

Belief-Guided Inference Control for Large Language Model Services via Verifiable Observations

arXiv:2604.27536v1 Announce Type: new Abstract: In black-box large language model (LLM) services, response reliability is often only partially observable at decision time, while stronger inference pat

safetyarxiv-cs-ai

1 May 2026

Prediction-powered Inference by Mixture of Experts

arXiv:2604.27892v1 Announce Type: cross Abstract: The rapidly expanding artificial intelligence (AI) industry has produced diverse yet powerful prediction tools, each with its own network architecture

1 May 2026

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters

arXiv:2602.17697v2 Announce Type: replace Abstract: Large Language Models (LLMs) are being increasingly used across a wide range of tasks. However, their substantial computational demands raise concer

29 Apr 2026

Tutorials

ZID-Net: Zero-Inference Diffusion Prior Decoupling Network for Single Image Dehazing

arXiv:2604.23709v1 Announce Type: new Abstract: Single image dehazing is often constrained by a trade-off between restoration quality and computational efficiency. While efficient, CNN networks strugg

tutorialsarxiv-cs-cv

28 Apr 2026

Time, Causality, and Observability Failures in Distributed AI Inference Systems

arXiv:2604.21361v1 Announce Type: new Abstract: Distributed AI inference pipelines rely heavily on timestamp-based observability to understand system behavior. This work demonstrates that even small c

safetyarxiv-cs-ai

24 Apr 2026

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

arXiv:2604.20735v1 Announce Type: new Abstract: Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertain

23 Apr 2026

Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference

arXiv:2604.20775v1 Announce Type: new Abstract: Trajectory Inference (TI) seeks to recover latent dynamical processes from snapshot data, where only independent samples from time-indexed marginals are

23 Apr 2026

Applications

Scalable AI Inference: Performance Analysis and Optimization of AI Model Serving

arXiv:2604.20420v1 Announce Type: cross Abstract: AI research often emphasizes model design and algorithmic performance, while deployment and inference remain comparatively underexplored despite being

applicationsarxiv-cs-ai

23 Apr 2026

Rate-Distortion Optimization for Transformer Inference

arXiv:2601.22002v3 Announce Type: replace Abstract: Transformers achieve superior performance on many tasks, but impose heavy compute and memory requirements during inference. This inference can be ma

21 Apr 2026

Symmetry Guarantees Statistic Recovery in Variational Inference

arXiv:2604.18310v1 Announce Type: cross Abstract: Variational inference (VI) is a central tool in modern machine learning, used to approximate an intractable target density by optimising over a tracta

21 Apr 2026

EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs

arXiv:2604.15787v1 Announce Type: cross Abstract: We introduce EVIL (extbf{EV}olving extbf{I}nterpretable algorithms with extbf{L}LMs), an approach that uses LLM-guided evolutionary search to discover

researcharxiv-cs-ai

20 Apr 2026

Faster LLM Inference via Sequential Monte Carlo

arXiv:2604.15672v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates language model inference by drafting tokens from a cheap proposal model and verifying them against an expensive

researcharxiv-cs-cl

20 Apr 2026

FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models

arXiv:2604.15488v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit undesirable behaviors, such as safety violations and hallucinations. Although inference-time steering offer

safetyarxiv-cs-ai

20 Apr 2026

Hardware

Thermodynamic Diffusion Inference with Minimal Digital Conditioning

arXiv:2604.14332v1 Announce Type: new Abstract: Diffusion-model inference and overdamped Langevin dynamics are formally identical. A physical substrate that encodes the score function therefore equili

hardwarearxiv-cs-lg

17 Apr 2026

Robust Federated Inference

arXiv:2510.00310v3 Announce Type: replace Abstract: Federated inference, in the form of one-shot federated learning, edge ensembles, or federated ensembles, has emerged as an attractive solution to co

local-aiarxiv-cs-lg

15 Apr 2026

FIT-GNN: Faster Inference Time for GNNs that 'FIT' in Memory Using Coarsening

arXiv:2410.15001v5 Announce Type: replace Abstract: Scalability of Graph Neural Networks (GNNs) remains a significant challenge. To tackle this, methods like coarsening, condensation, and computation

13 Apr 2026

Active Statistical Inference

arXiv:2403.03208v3 Announce Type: replace-cross Abstract: Inspired by the concept of active learning, we propose active inferencenicode{x2013}a methodology for statistical inference with machine-l

10 Apr 2026

Conditional Mean Flows: Few-Step Densities for Simulation-Based Inference

arXiv:2610.21657v1 Announce Type: cross Abstract: Flow matching has emerged as a powerful generative family for simulation-based inference (SBI). However, sampling and density evaluation require numer

16 Oct 2026

Fractional Power-of-Two Quantization for Efficient and Effective Multiplier-Free LLM Inference

model-releasesarxiv-cs-ai

arXiv:2610.21257v1 Announce Type: cross Abstract: Large Language Models (LLMs) demand efficient inference, where the multiply-accumulate (MAC) operations in linear projections dominate compute and ene

16 Oct 2026

Applications

Graph Dirichlet Energy for Fitting-Free Bivariate Causal Inference

arXiv:2610.21892v1 Announce Type: new Abstract: We propose the Graph Dirichlet Energy Causal Inference (GDECI) criterion for distinguishing cause from effect in bivariate settings. For a candidate dir

applicationsarxiv-cs-lg

16 Oct 2026

Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes

arXiv:2610.19053v1 Announce Type: new Abstract: Inference of phylogenetic trees from sequences plays a central role in understanding evolutionary relationships, with applications ranging from tracking

15 Oct 2026

Seamless Deployment of Machine Learning Inference at the Far Edge: An Empirical AWS IoT Greengrass Architecture for Industrial Predictive Maintenance

arXiv:2610.14815v1 Announce Type: cross Abstract: Industrial IoT sensors produce continuous, high-volume data streams that predictive maintenance needs to analyse in real time. Cloud-centric architect

local-aiarxiv-cs-ai

15 Oct 2026

Agents

Two Routes to Interoceptive Prioritisation: Dissociating Likelihood Precision and Preference Reweighting in Active Inference

arXiv:2610.18617v1 Announce Type: new Abstract: An embodied agent must prioritise among competing bodily needs. In active inference, it can respond to an urgent need by increasing the precision of inf

agentsarxiv-cs-ai

15 Oct 2026

Closing the Estimation Gap: Training-Free Transductive Inference for Cross-Domain Few-Shot Action Recognition

arXiv:2610.18209v1 Announce Type: new Abstract: Cross-domain few-shot action recognition (CD-FSAR) aims to recognise unseen action classes in a target domain from a handful of labelled videos. Despite

researcharxiv-cs-cv

14 Oct 2026

Constrained Diffusion Models with Primal-Dual Inference

arXiv:2606.17192v2 Announce Type: replace Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimi

safetyarxiv-cs-lg

14 Oct 2026

Probe and Skip: Self-Predictive Token Skipping for Efficient Long-Context LLM Inference

arXiv:2601.13155v3 Announce Type: replace-cross Abstract: Long-context inference enhances the reasoning capability of Large Language Models (LLMs), but incurs significant computational overhead. Token

14 Oct 2026

Power Side-Channel Membership Inference Attack on Embedded Machine Learning