Search: “inference”

CARE: Certifying Acceleration for Vision-Language-Action Inference

arXiv:2610.08917v1 Announce Type: new Abstract: While vision-language-action (VLA) models have advanced rapidly, running them at every control step remains expensive. Prior work accelerates VLA infere

8 Oct 2026

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Research

Hierarchy-GBP: Accelerating Factor Graph Inference via Abstraction and Recovery

DGX agent

arXiv:2610.06978v1 Announce Type: new Abstract: Gaussian Belief Propagation (GBP) is a distributed inference algorithm that passes messages in graphical models, making it attractive for scalable spati

researcharxiv-cs-cv

7 Oct 2026

Local Ai

Inference-Time Projection for Physically Valid Biomolecular Diffusion Models

arXiv:2610.07037v1 Announce Type: new Abstract: AlphaFold 3-style cofolding models predict biomolecular complexes with high structural accuracy, yet a large fraction of their outputs are physically in

local-aiarxiv-cs-ai

Agents

Large Language Model Orchestration under Heterogeneous Preferences via Explicit Persona Inference

arXiv:2610.07587v1 Announce Type: new Abstract: LLM orchestration investigates how an orchestrator coordinates a group of autonomous agents to achieve common goals or maximize collective welfare. The

agentsarxiv-cs-cl

Prediction-powered inference for time series across space

arXiv:2610.08715v1 Announce Type: cross Abstract: The following motif is common in spatiotemporal settings: we have a sequence of covariate and label pairs observed for a relatively short, recent time

ProximalFM: Amortized Proximal Causal Inference under Hidden Confounding

arXiv:2610.08078v1 Announce Type: cross Abstract: Standard causal identification methods often assume no unmeasured confounding and can fail when relevant confounders are unobserved. Proximal causal i

Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks

arXiv:2610.03741v1 Announce Type: cross Abstract: Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks becaus

6 Oct 2026

TreeWalker: Partial Evaluation for Grouped Tree-Ensemble Inference

arXiv:2610.03939v1 Announce Type: new Abstract: Many inference workloads evaluate a trained tree ensemble on row groups that share feature values: discrete-time survival models expand each patient int

6 Oct 2026

LatticeSMC: Where to Spend Inference-Time Compute in Chunked Sequence Generators

arXiv:2610.02774v1 Announce Type: new Abstract: Long-form generators for music, motion and video produce sequences chunk by chunk, with each chunk generated by iterative denoising while rewards are de

5 Oct 2026

OLMo-Detect: A Multi-Stage, Confounder-Controlled Benchmark for Membership Inference on Large Language Models

arXiv:2610.02986v1 Announce Type: new Abstract: Membership inference on large language models (LLMs) aims to determine whether a given text sample was included in an LLM's training data, without acces

5 Oct 2026

TopK-Guided: Adaptive, Budget-Aware Activation Sparsity for Efficient LLM Inference

arXiv:2610.01763v1 Announce Type: new Abstract: Activation sparsity speeds up large language model (LLM) inference by setting unimportant activations to zero so that the corresponding computations can

2 Oct 2026

Agents

Embodiment-aware control by inference over the operator: a simulation study

arXiv:2609.38437v1 Announce Type: new Abstract: Teleoperation systems are tuned for channel fidelity, while whether the operator experiences the device as part of the body, the Sense of Embodiment (So

agentsarxiv-cs-ro

1 Oct 2026

Steepest Guidance: A Practical and Principled Approach to Inference-Time Alignment of Flow and Diffusion-based Models

arXiv:2609.39091v1 Announce Type: cross Abstract: Inference-time alignment of flow and diffusion-based models is critical for achieving flexible generative modeling. Theoretically, Doob's h-transform

1 Oct 2026

Federation of Experts: Communication Efficient Distributed Inference for Large Language Models

arXiv:2605.06206v2 Announce Type: replace Abstract: Mixture of experts has emerged as the primary mechanism for making Large Language Models (LLMs) computationally efficient. However, in distributed s

hardwarearxiv-cs-lg

30 Sept 2026

FluxLite: Inference-Time Proposal Control for Discrete Diffusion Models

arXiv:2609.35947v1 Announce Type: new Abstract: Many inference-time tasks for pretrained discrete diffusion models and diffusion language models reduce to drawing samples from a tilted version of the

30 Sept 2026

Post-Anomaly Detection Inference for Deep SVDD

arXiv:2609.37935v1 Announce Type: cross Abstract: Deep Support Vector Data Description (Deep SVDD) has become a prominent framework for unsupervised anomaly detection by learning latent representation

30 Sept 2026

Fiona: Accelerating FHE Inference with Packing-Aware Ternary Weights

arXiv:2609.35352v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables neural network inference directly on encrypted inputs, but it remains orders of magnitude slower than plainte

29 Sept 2026

Applications

Transfer Calibrated Prediction Powered Inference

arXiv:2609.34156v1 Announce Type: new Abstract: Prediction-powered inference (PPI) and its power-tuned extension (PPI++) improve confidence intervals by combining a small gold-standard labeled sample

applicationsarxiv-cs-lg

29 Sept 2026

Learning the Cost of Reliable Inference

arXiv:2609.28322v1 Announce Type: new Abstract: Benchmarking and routing platforms increasingly act as intermediaries connecting large language model providers with end-users. However, providers on th

24 Sept 2026

Local Ai

Partner-Specific Affective Precision in Social Active Inference

arXiv:2609.24876v1 Announce Type: new Abstract: In multi-agent social settings, model reliability varies across relationships. Beyond inferring what others will do, an agent must calibrate how confide

local-aiarxiv-cs-ai

23 Sept 2026

RoofLang: Enabling AI-Driven Architecting of LLM Inference Systems

arXiv:2609.12551v2 Announce Type: replace-cross Abstract: AI is beginning to make substantive contributions to LLM inference optimization. Existing AI optimizations are predominantly profiling-based.

23 Sept 2026

Variational objectives for amortized Bayesian inference in inverse problems: The role of posterior conditioning

arXiv:2609.25145v1 Announce Type: cross Abstract: Variational autoencoders (VAEs) offer an efficient approach to amortized Bayesian inference for inverse problems, but posterior accuracy can depend st

23 Sept 2026

Causal Inference with Unobserved Confounding: A Mixture Learning Perspective

arXiv:2609.23219v1 Announce Type: new Abstract: Unobserved confounding is a fundamental challenge in causal inference from observational data. This article develops a mixture-learning perspective, vie

22 Sept 2026

Applications

React When You Need To: Event-Triggered Asynchronous Inference for VLA Policies

arXiv:2609.22587v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models commonly predict action chunks, limiting their ability to react to environmental changes during execution. Existing

applicationsarxiv-cs-ro

22 Sept 2026

The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a

hardwarearxiv-cs-ai

17 Sept 2026

FlexEE: Self-Speculative and KV-Compatible Early Exiting for Offloading-Aware LLM Inference

arXiv:2609.17008v1 Announce Type: new Abstract: Large language model (LLM) inference is often constrained by both computation and memory, especially in offloading-based deployments where model weights

16 Sept 2026

One Size Does Not Fit All: Setting Inference Depth from the Questions a Deployment Actually Asks

arXiv:2609.14144v1 Announce Type: new Abstract: A transformer language model is trained to respond to any prompt, but each deployment asks only a narrow range of questions: a support assistant sees de

15 Sept 2026

Self-Orchestrating Language Models: Leveraging Semantic Dependence for Efficient Inference

arXiv:2609.14850v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate impressive capabilities, but their deployment presents significant efficiency challenges. Autoregressive decodi

15 Sept 2026

GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs

arXiv:2609.12448v1 Announce Type: new Abstract: Sensitive attributes such as age, income, and occupation can be inferred from user-generated content by aggregating indirect cues across many ordinary p

14 Sept 2026

Inference-Time Nash Alignment

arXiv:2609.08082v1 Announce Type: new Abstract: Preference-based fine-tuning methods such as RLHF and DPO require substantial compute and large preference datasets. They also need direct access to the

10 Sept 2026

Optimal Value Inference for Reinforcement Learning

arXiv:2609.09981v1 Announce Type: cross Abstract: We study offline inference for the optimal value in reinforcement learning. Two new nuisances are derived as fixed points of a self-induced Bellman eq

10 Sept 2026

Confounding-Valid Conformal Inference for Counterfactual KPIs in Wireless Networks

arXiv:2609.05073v1 Announce Type: new Abstract: Conformal counterfactual inference enables network operators to use logged telemetry to reliably answer 'what-if' questions about network operation. The

7 Sept 2026

Self-Supervised Lexical Representation Learning for Fast, Large-Scale Phylogenetic Inference

arXiv:2609.05262v1 Announce Type: new Abstract: Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a global scale remains constrained by two fac

hardwarearxiv-cs-cl

7 Sept 2026

Agents

A Survey on Self-Improving Test-Time Intelligence: Feedback-Driven Adapting, Learning, and Scaling at Inference

arXiv:2609.01679v1 Announce Type: new Abstract: The ability of AI systems to improve their behavior during deployment is becoming increasingly important. As inference moves beyond the static execution

agentsarxiv-cs-lg

3 Sept 2026

Local Ai

GeoSPRINT: Geometric Redundancy-Aware Step Pruning for Inference in Diffusion Trajectories

arXiv:2609.02160v1 Announce Type: cross Abstract: Diffusion models achieve high sample quality but remain expensive at inference time because sampling requires many sequential neural function evaluati

local-aiarxiv-cs-ai

3 Sept 2026

Beyond Tokens: Semantic-Aware Speculative Decoding for Efficient Inference by Probing Internal States

arXiv:2602.03708v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance across many tasks but suffer from high inference latency due to autoregressive decoding. The

researcharxiv-cs-cl

DynaNDE: Dynamic Near-Data Expert Scheduling for Batched MoE Inference

arXiv:2609.00407v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable efficient scaling of large language model (LLM) inference but suffer from substantial data-movement overhead wh

PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition

arXiv:2609.01024v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures scale Large Language Model (LLM) capacity efficiently by activating a sparse subset of experts per token. However

researcharxiv-cs-cl

Position Matters: Feature Inversion Attacks in ViT Split Inference with Token Reduction and Shuffling

arXiv:2609.01232v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are increasingly used in split-inference systems, where edge devices transmit intermediate token representations to a remot

CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration

arXiv:2608.30295v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in handling long-context tasks, but processing such long contexts remains challengi

1 Sept 2026

Kascade: A Practical Sparse Attention Method for Long-Context LLM Inference

arXiv:2512.16391v2 Announce Type: replace-cross Abstract: Attention is the dominant source of latency during long-context LLM inference, an increasingly popular workload with reasoning models and RAG.

hardwarearxiv-cs-ai

1 Sept 2026

Layered LLM Defenses as an Ensemble: Access Tiers, Inference Cost, and the Measured Failure Correlation Between Defense Layers

arXiv:2608.28327v1 Announce Type: cross Abstract: Practitioners defend large language models (LLMs) by stacking defenses, assuming the layers compound. A stack is an ensemble, and ensembles compound o

researcharxiv-cs-cl

31 Aug 2026

Privacy Without Regret: Differentially Private Inference-Time Alignment

arXiv:2608.26324v1 Announce Type: new Abstract: Best-of-N (BoN) sampling is the simplest and most widely deployed inference-time alignment strategy, but it suffers from two distinct problems: reward h

28 Aug 2026

CST: Collaborative Selective Transmission for Communication-Efficient Multimodal Edge Inference

arXiv:2608.22115v1 Announce Type: new Abstract: Collaborative multimodal inference improves edge perception by combining observations from distributed sensing devices, but transmitting high-dimensiona

hardwarearxiv-cs-lg

25 Aug 2026

Spatio-Temporal Parallelism for Diffusion Model Inference on Heterogeneous Multi-GPU Systems

arXiv:2509.04719v3 Announce Type: replace-cross Abstract: The widespread adoption of diffusion models for image generation necessitates efficient parallel inference to manage their substantial computa

hardwarearxiv-cs-cv

25 Aug 2026

Token-Level Likelihood-Array Regression for Membership Inference and AI-Generated Text Detection

arXiv:2608.22179v1 Announce Type: cross Abstract: Membership inference asks whether a text was used to train a language model, whereas AI-generated text detection asks whether it was generated by a la

25 Aug 2026

TracingFlow: A Simulation-Free Trajectory Inference Framework Based on Second-Order Dynamics

arXiv:2608.21070v1 Announce Type: cross Abstract: Inferring continuous system evolution from sparse temporal snapshots is a key challenge in generative modeling and single-cell omics. While Optimal Tr

24 Aug 2026

Discrete Diffusion Inference-Time Control with Nested Sequential Monte Carlo

arXiv:2608.20123v1 Announce Type: cross Abstract: We study inference-time control for text generation in discrete diffusion language models, where the goal is to steer sampling toward sequence-level r