Search: “inference”

arXiv:2605.16397v1 Announce Type: cross Abstract: The increasing integration of sensors in autonomous maritime navigation has led to large-scale multimodal datasets, raising challenges in achieving ef

agentsarxiv-cs-ai

19 May 2026

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Going Beyond the Edge: Distributed Inference of Transformer Models on Ultra-Low-Power Wireless Devices

DGX agent

arXiv:2605.15694v1 Announce Type: new Abstract: Transformer models are rapidly becoming a cornerstone of modern Internet of Things (IoT) applications, yet their computational and memory demands far ex

applicationsarxiv-cs-lg

18 May 2026

Training-Free Inference for High-Resolution Sinogram Completion

arXiv:2506.08809v5 Announce Type: replace Abstract: High-resolution sinogram completion is critical for computed tomography reconstruction, as missing projections can introduce severe artifacts. While

local-aiarxiv-cs-cv

15 May 2026

Attention Once Is All You Need: Efficient Streaming Inference with Stateful Transformers

arXiv:2605.13784v1 Announce Type: new Abstract: Conventional transformer inference engines are request-driven, paying an O(n) prefill cost on every query. In streaming workloads, where data arrives co

14 May 2026

Temper and Tilt Lead to SLOP: Reward Hacking Mitigation with Inference-Time Alignment

arXiv:2605.13537v1 Announce Type: cross Abstract: Inference-time alignment techniques offer a lightweight alternative or complement to costly reinforcement learning, while enabling continual adaptatio

safetyarxiv-cs-ai

14 May 2026

Active inference as a unified model of collision avoidance behavior in human drivers

arXiv:2506.02215v5 Announce Type: replace Abstract: Collision avoidance -- involving a rapid threat detection and quick execution of the appropriate evasive maneuver -- is a critical aspect of driving

researcharxiv-cs-ro

Tutorials

FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models

arXiv:2605.11527v1 Announce Type: new Abstract: Diffusion models are the leading approach for tabular data synthesis and are increasingly used to share sensitive records. Whether they actually protect

tutorialsarxiv-cs-lg

LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows

arXiv:2605.11368v1 Announce Type: new Abstract: We study the application of recent Edit Flows for inference-time reward control for DNA sequence generation. Unlike most reward-guided DNA generation fr

local-aiarxiv-cs-lg

Why Conclusions Diverge from the Same Observations: Formalizing World-Model Non-Identifiability via an Inference

arXiv:2605.12255v1 Announce Type: cross Abstract: When people share the same documents and observations yet reach different conclusions, the disagreement often shifts into a judgment that the other pa

Active Multiple-Prediction-Powered Inference

arXiv:2605.08429v1 Announce Type: cross Abstract: Post-deployment monitoring of healthcare AI requires statistically valid, label-efficient methods, but gold-standard labels from clinician chart revie

Capacity-Aware Inference: Mitigating the Straggler Effect in Mixture of Experts

model-releasesarxiv-cs-ai

arXiv:2503.05066v5 Announce Type: replace-cross Abstract: The Mixture of Experts (MoE) is an effective architecture for scaling large language models by leveraging sparse expert activation to balance

Foundations of Reliable Inference: Reliability-Efficiency Co-Design

arXiv:2605.10351v1 Announce Type: new Abstract: Reliable inference requires that artificial intelligence (AI) models provide trustworthy uncertainty estimates, not merely accurate predictions. Recent

Nested Slice Sampling: Vectorized Nested Sampling for GPU-Accelerated Inference

arXiv:2601.23252v2 Announce Type: replace-cross Abstract: Model comparison and calibrated uncertainty quantification often require integrating over parameters, but scalable inference can be challengin

ORICF -- Open Robotics Inference and Control Framework

arXiv:2605.09656v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) have enabled effective perception and language models for robots, but their deployment remains computati

researcharxiv-cs-ro

Reasoning emerges from constrained inference manifolds in large language models

model-releasesarxiv-cs-cl

arXiv:2605.08142v1 Announce Type: cross Abstract: Reasoning in large language models is predominantly evaluated through labeled benchmarks, conflating task performance with the quality of internal inf

Supercharging Bayesian Inference with Reliable AI-Informed Priors

arXiv:2605.09834v1 Announce Type: cross Abstract: Modern predictive systems encode beliefs that can act as useful prior information for statistical inference in data-limited settings. Using them for p

safetyarxiv-cs-lg

Understand and Accelerate Memory Processing Pipeline for Disaggregated LLM Inference

arXiv:2603.29002v2 Announce Type: replace-cross Abstract: Modern large language models (LLMs) increasingly depends on efficient long-context processing and generation mechanisms, including sparse atte

hardwarearxiv-cs-ai

An Efficient Hybrid Sparse Attention with CPU-GPU Parallelism for Long-Context Inference

arXiv:2605.07719v1 Announce Type: cross Abstract: Long-context inference increasingly operates over CPU-resident KV caches, either because decoding-time KV states exceed GPU memory capacity or because

hardwarearxiv-cs-ai

Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priors

arXiv:2605.07993v1 Announce Type: new Abstract: Causal inference, especially in observational studies, relies on untestable assumptions about the true data-generating process. Sensitivity analysis hel

Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation

arXiv:2605.07985v1 Announce Type: cross Abstract: Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, s

hardwarearxiv-cs-ai

SGD for Variational Inference: Tackling Unbounded Variance via Preconditioning and Dynamic Batching

arXiv:2605.07531v1 Announce Type: new Abstract: Black-Box Variational Inference (BBVI) typically relies on Stochastic Gradient Descent (SGD) to optimize the Evidence Lower Bound (ELBO). However, the s

Sparse Attention as a Range Searching Problem: Towards an Inference-Efficient Index for KV Cache

arXiv:2605.06763v1 Announce Type: new Abstract: Sparse attention improves LLM inference efficiency by selecting a subset of key-value entries, but at the cost of potential accuracy degradation. In par

hardwarearxiv-cs-lg

GraphPI: Efficient Protein Inference with Graph Neural Networks

arXiv:2605.04376v1 Announce Type: new Abstract: The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite thes

7 May 2026

Agents

LAWS: Learning from Actual Workloads Symbolically -- A Self-Certifying Parametrized Cache Architecture for Neural Inference, Robotics, and Edge Deployment

arXiv:2605.04069v1 Announce Type: new Abstract: We introduce LAWS (Learning from Actual Workloads Symbolically), a self-certifying inference caching architecture that builds a growing library of certi

agentsarxiv-cs-lg

7 May 2026

Predict-then-Diffuse: Adaptive Response Length for Compute-Budgeted Inference in Diffusion LLMs

arXiv:2605.04215v1 Announce Type: new Abstract: Diffusion-based Large Language Models (D-LLMs) represent a promising frontier in generative AI, offering fully parallel token generation that can lead t

safetyarxiv-cs-lg

7 May 2026

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding

arXiv:2505.24791v2 Announce Type: replace Abstract: Discrete normalizing flows are promising generative models with advantages such as analytical log-likelihood computation and end-to-end training. Ho

6 May 2026

Hey, That's My Data! Token-Only Dataset Inference in Large Language Models

arXiv:2506.06057v2 Announce Type: replace Abstract: Large Language Models (LLMs) rely on massive training datasets, often including proprietary data, which raises concerns about unauthorized usage and

P3-LLM: An Integrated NPU-PIM Accelerator for Edge LLM Inference Using Hybrid Numerical Formats

arXiv:2511.06838v4 Announce Type: replace-cross Abstract: The substantial memory bandwidth and computational demands of large language models (LLMs) present critical challenges for efficient inference

Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference

arXiv:2511.08303v2 Announce Type: replace-cross Abstract: This study investigates treatment effect estimation in the semi-supervised setting, also can be interpreted as prediction-powered inference. I

Silicon Showdown: Performance, Efficiency, and Ecosystem Barriers in Consumer-Grade LLM Inference

model-releasesarxiv-cs-ai

arXiv:2605.00519v2 Announce Type: cross Abstract: The operational landscape of local Large Language Model (LLM) inference has shifted from lightweight models to datacenter-class weights exceeding 70B

Token Arena: A Continuous Benchmark Unifying Energy and Cognition in AI Inference

arXiv:2605.00300v1 Announce Type: cross Abstract: Public inference benchmarks compare AI systems at the model and provider level, but the unit at which deployment decisions are actually made is the en

4 May 2026

Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection

arXiv:2602.03216v2 Announce Type: replace Abstract: The quadratic complexity of attention remains the central bottleneck in long-context inference for large language models. Prior acceleration methods

4 May 2026

TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference

arXiv:2505.11329v5 Announce Type: replace-cross Abstract: Distributed inference of large language models (LLMs) using tensor parallelism can introduce communication overheads of 20% even over GPUs con

local-aiarxiv-cs-lg

4 May 2026

Multibit neural inference in a N-ary crossbar architecture

arXiv:2604.26979v1 Announce Type: cross Abstract: In-memory computing (IMC) enables energy-efficient neural network inference by computing analog matrix-vector multiplications (MVM) in memory crossbar

1 May 2026

DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference

arXiv:2604.26557v1 Announce Type: cross Abstract: The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key cha

local-aiarxiv-cs-ai

30 Apr 2026

Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery

arXiv:2502.14912v2 Announce Type: replace Abstract: We present a framework for generating universal semantic embeddings of chemical elements to advance materials inference and discovery. This framewor

30 Apr 2026

ToolPRM: Fine-Grained Inference Scaling of Structured Outputs for Function Calling

arXiv:2510.14703v2 Announce Type: replace Abstract: Large language models (LLMs) excel at function calling, but inference scaling has been explored mainly for unstructured generation. We propose an in

30 Apr 2026

Comparing Data Assimilation and Likelihood-Based Inference on Latent State Estimation in Agent-Based Models

arXiv:2509.17625v2 Announce Type: replace Abstract: In this paper, we present the first systematic comparison of Data Assimilation (DA) and Likelihood-Based Inference (LBI) in the context of an Agent-

29 Apr 2026

DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference

arXiv:2510.19669v4 Announce Type: replace Abstract: Recent reasoning Large Language Models (LLMs) demonstrate remarkable problem-solving abilities but often generate long thinking traces whose utility

29 Apr 2026

Heterogeneous Variational Inference for Markov Degradation Hazard Models: Discretized Mixture with Interpretable Clusters

arXiv:2604.24818v1 Announce Type: new Abstract: Bayesian finite mixture models can identify discrete risk clusters (low-risk vs. high-risk equipment), but face three critical bottlenecks: (1) insuffic

29 Apr 2026

DepthKV: Layer-Dependent KV Cache Pruning for Long-Context LLM Inference

arXiv:2604.24647v1 Announce Type: cross Abstract: Long-context reasoning is a critical capability of large language models (LLMs), enabling applications such as long-document understanding, summarizat

GeoFunFlow-3D: A Physics-Guided Generative Flow Matching Framework for High-Fidelity 3D Aerodynamic Inference over Complex Geometries

arXiv:2604.23350v1 Announce Type: cross Abstract: Deep generative models and neural operators have demonstrated significant potential for 3D aerodynamic inference. However, they often face inherent ch

local-aiarxiv-cs-lg

Hybrid JIT-CUDA Graph Optimization for Low-Latency Large Language Model Inference

model-releasesarxiv-cs-ai

arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con

MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback

arXiv:2604.23107v1 Announce Type: cross Abstract: Causal effect estimation from observational data requires careful adjustment for confounding. Classical estimators such as inverse probability weighti

Score-based Membership Inference on Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2509.25003v2 Announce Type: replace-cross Abstract: Membership inference attacks (MIAs) against Diffusion Models (DMs) raise pressing privacy concerns by revealing whether a sample was part of t

27 Apr 2026

Efficient Test-Time Inference via Deterministic Exploration of Truncated Decoding Trees

arXiv:2604.20500v1 Announce Type: new Abstract: Self-consistency boosts inference-time performance by sampling multiple reasoning traces in parallel and voting. However, in constrained domains like ma

23 Apr 2026

Generalization and Membership Inference Attack a Practical Perspective

arXiv:2604.19936v1 Announce Type: cross Abstract: With the emergence of new evaluation metrics and attack methodologies for Membership Inference Attacks (MIA), it becomes essential to reevaluate previ

23 Apr 2026

Lever: Inference-Time Policy Reuse under Support Constraints