Search: “inference”

Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective

arXiv:2505.20955v4 Announce Type: replace-cross Abstract: Diffusion models have achieved tremendous success in image generation, but they also raise significant concerns regarding privacy and copyrigh

29 May 2026

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Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference

DGX agent

arXiv:2510.24606v2 Announce Type: replace Abstract: The quadratic cost of attention limits the scalability of long-context LLMs, especially under limited hardware memory budgets. While attention is of

model-releasesarxiv-cs-cl

29 May 2026

Calibrated Inference for the Conditional Average Treatment Effect in the Few-Placebo Regime via Gaussian Processes

arXiv:2605.27473v1 Announce Type: cross Abstract: Estimating how much an intervention helps a given individual the conditional average treatment effect (CATE) is increasingly central to decision-makin

safetyarxiv-cs-lg

28 May 2026

Learning with Importance Weighted Variational Inference

arXiv:2410.12035v2 Announce Type: replace-cross Abstract: Several variational bounds involving importance weighting ideas generalize the Evidence Lower BOund (ELBO) for marginal likelihood optimizatio

safetyarxiv-cs-lg

28 May 2026

Meta-Attention: Bayesian Per-Token Routing for Efficient Transformer Inference

arXiv:2605.28384v1 Announce Type: new Abstract: Standard transformer architectures apply a single attention mechanism uniformly across all tokens and sequence positions, irrespective of local context

28 May 2026

BUILD with Precision: Bottom-Up Inference of Linear DAGs

arXiv:2512.16111v2 Announce Type: replace Abstract: Learning the structure of directed acyclic graphs (DAGs) from observational data is a central problem in causal discovery, statistical signal proces

Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction

arXiv:2510.03352v3 Announce Type: replace-cross Abstract: Diffusion models have been used as priors for solving inverse problems. However, existing approaches typically overlook side information that

MVISTA-4D: View-Consistent 4D World Model with Test-Time Action Inference for Robotic Manipulation

arXiv:2602.09878v2 Announce Type: replace Abstract: World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely im

safetyarxiv-cs-cv

Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications

arXiv:2605.26133v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become the predominant paradigm in NLP, advancing both research and industry. As model sizes and pretraining data gr

Vectors Are Not Neutral: Sensitive-Information Inference from Exported LLM Representations in Summarization

model-releasesarxiv-cs-cl

arXiv:2605.26433v1 Announce Type: new Abstract: Large language model (LLM) summarization systems may pass compact vector representations of private inputs to downstream retrieval, monitoring, audit, o

VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models

arXiv:2510.17759v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) extend large language models with visual reasoning, but their multimodal design also introduces new, underexplor

safetyarxiv-cs-cl

Conformalised imprecise inference for robust extrapolation under limited data

arXiv:2605.25882v1 Announce Type: new Abstract: Recent advances in uncertainty quantification increasingly emphasise the distinction between aleatory and epistemic uncertainty in machine learning, mot

Is Inference Mediated by Distinct Semantic Structures in LLMs? A Mechanistic Interpretation

arXiv:2605.25520v1 Announce Type: new Abstract: Predicting a label correctly does not necessarily require representing the operation that produces it. Transformer representations are known to carry la

researcharxiv-cs-cl

Robust inference using density-powered Stein operators

arXiv:2511.03963v2 Announce Type: replace-cross Abstract: We introduce a density-power weighted variant for the Stein operator, called the gamma-Stein operator. This is a novel class of operators deri

Statistical Inference for Stochastic Gradient Descent Beyond Finite Variance

arXiv:2605.26000v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is a foundational algorithm for large-scale statistical learning and stochastic optimization. However, statistical i

SpinFlow: A Physics-Informed Spin Field Framework for Traffic Phase Inference and Transition Detection

arXiv:2605.23306v1 Announce Type: cross Abstract: Active traffic management (ATM) is frequently hindered by traditional macroscopic models and rigid empirical thresholds that fail to capture metastabl

safetyarxiv-cs-lg

25 May 2026

Asymmetric Virtual Memory Paging for Hybrid Mamba-Transformer Inference

arXiv:2605.22416v1 Announce Type: new Abstract: Hybrid language models like Jamba mix attention layers with State Space Models (SSMs), creating two memory cache types with opposite profiles: Key-Value

Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model

arXiv:2605.21568v1 Announce Type: new Abstract: In this work, we extend the Equilibrium Propagation framework to skew-gradient systems and show an equivalence between deep Energy-Based Models and Hami

Tutorials

PhylaFlow: Hybrid Flow Matching in Billera-Holmes-Vogtmann Tree Space for Phylogenetic Inference

arXiv:2605.21859v1 Announce Type: cross Abstract: Phylogenetic trees are hybrid objects: branch lengths vary continuously, while topologies change discretely through edge contractions and expansions.

tutorialsarxiv-cs-lg

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference

arXiv:2605.22162v1 Announce Type: cross Abstract: Stellar spectra encode key information on the physical properties and chemical compositions of stars. Accurate stellar parameter determination is esse

CrossVLA: Cross-Paradigm Post-Training and Inference Optimization for Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2605.21854v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have rapidly converged on a small set of architectural patterns: discrete-token autoregression (e.g. OpenVLA) and co

22 May 2026

Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment

arXiv:2605.22677v1 Announce Type: new Abstract: Deploying vision models across devices with varying resource constraints, or even on a single device where available compute fluctuates due to battery s

researcharxiv-cs-cv

22 May 2026

Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health

arXiv:2605.20782v1 Announce Type: new Abstract: Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurre

Diffusion Models Memorize in Training -- and Generalize in Inference

arXiv:2603.13419v2 Announce Type: replace Abstract: Diffusion models generalize well in practice. However, an optimal diffusion model fully memorizes the training data and therefore fails to generaliz

local-aiarxiv-cs-lg

E-ReCON: An Energy- and Resource-Efficient Precision-Configurable Sparse nvCIM Macro for Conventional and Spiking Neural Edge Inference

arXiv:2605.20717v1 Announce Type: cross Abstract: This work presents E-ReCON, a 16 Kb energy and resource-efficient digital compute-in-memory (DCIM) macro based on a compact 3T1R ReRAM bitcell for edg

local-aiarxiv-cs-cv

FlowLong: Inference-time Long Video Generation via Manifold-constrained Tweedie Matching

arXiv:2605.20910v1 Announce Type: new Abstract: Extending the generation horizon of video diffusion models to long sequences remains a long-standing and important challenge. Existing training-free app

safetyarxiv-cs-cv

Hardware

Frontier: Towards Comprehensive and Accurate LLM Inference Simulation

arXiv:2605.21312v1 Announce Type: cross Abstract: Modern LLM serving is no longer homogeneous or monolithic. Production systems now combine disaggregated execution, complex parallelism, runtime optimi

hardwarearxiv-cs-lg

Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU

arXiv:2605.20706v1 Announce Type: cross Abstract: Running language models in the browser presents a unique opportunity to build efficient, private, and portable AI applications, but requires contendin

Memory-Efficient Partitioned DNN Inference on Resource-Constrained Android Crowds

arXiv:2605.20723v1 Announce Type: new Abstract: Deploying large deep neural networks on memory-constrained mobile devices is a central challenge in edge ML. While compression, pruning, and quantizatio

Uncertainty-Guided Conservative Propagation for Structured Inference in Vessel Segmentation

arXiv:2605.20543v1 Announce Type: new Abstract: Accurate vessel segmentation is essential for medical image analysis, yet remains challenging due to complex vascular patterns and imaging ambiguity. Mo

researcharxiv-cs-cv

Hardware

Accelerating Sparse Transformer Inference on GPU

arXiv:2506.06095v4 Announce Type: replace Abstract: Large language models (LLMs) are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerat

hardwarearxiv-cs-lg

Applications

Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors

arXiv:2605.18927v1 Announce Type: cross Abstract: Bayesian latent space models offer a principled approach to network representation, but rely on correct specification of both geometry and link functi

applicationsarxiv-cs-lg

CounterFlow: A Two-Phase Inference-Time Sampling for Counterfactual Video Foley Generation

arXiv:2605.18916v1 Announce Type: cross Abstract: We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining

Distributionally Robust Control via Stein Variational Inference for Contact-Rich Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.19029v1 Announce Type: new Abstract: Reliable robotic manipulation requires control policies that can accurately represent and adapt to uncertainty arising from contact-rich interactions. M

Tutorials

FAWN: A MultiEncoder Fusion-Attention Wave Network for Integrated Sensing and Communication Indoor Scene Inference

arXiv:2509.14968v3 Announce Type: replace Abstract: The upcoming generations of wireless technologies promise an era where everything is interconnected and intelligent. As the need for intelligence gr

tutorialsarxiv-cs-lg

Tutorials

INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference

arXiv:2605.18853v1 Announce Type: cross Abstract: Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but

tutorialsarxiv-cs-cv

PRISM-SLAM: Probabilistic Ray-Grounded Inference for Scale-aware Metric SLAM

arXiv:2605.19257v1 Announce Type: new Abstract: Monocular SLAM historically suffers from scale ambiguity and tracking failure in dynamic environments. While recent vision foundation models (VFMs) prov

local-aiarxiv-cs-ro

Membership Inference Attacks on Discrete Diffusion Language Models

model-releasesarxiv-cs-ai

arXiv:2605.16445v1 Announce Type: cross Abstract: Masked Diffusion Language Models MDLMs replace autoregressive generation with iterative demasking and their privacy properties are largely unstudied.

Public-Decay Homomorphic State Space Models for Private Sequence Inference

arXiv:2605.16647v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) changes sequence-model design because rotations, encrypted products, ciphertext materialization, multiplicative dep

local-aiarxiv-cs-lg

Applications

Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling

arXiv:2605.18007v1 Announce Type: new Abstract: Rhetorical Role Labeling (RRL) assigns a functional role to each sentence in a document and is widely used in legal, medical, and scientific domains. Wh

applicationsarxiv-cs-cl

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment

arXiv:2605.17341v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved remarkable success, yet their reliance on massive datasets and unintended memorization of training data ra

safetyarxiv-cs-ai

FAR: Function-preserving Attention Replacement for IMC-friendly Inference

arXiv:2505.21535v4 Announce Type: replace-cross Abstract: While transformers dominate modern vision and language models, their attention mechanism remains poorly suited for in-memory computing (IMC) d

local-aiarxiv-cs-ai

18 May 2026

Grokking as Structural Inference: Transformers Need Bayesian Lottery Tickets

arXiv:2605.15787v1 Announce Type: cross Abstract: Why does a Transformer that has memorized its training set wait thousands of steps before it generalizes? Existing accounts locate this delay in norm

18 May 2026

Compositional Video Generation via Inference-Time Guidance

arXiv:2605.14988v1 Announce Type: new Abstract: Text-to-video diffusion models generate realistic videos, but often fail on prompts requiring fine-grained compositional understanding, such as relation

researcharxiv-cs-cv

Diagnosing Training Inference Mismatch in LLM Reinforcement Learning

arXiv:2605.14220v1 Announce Type: cross Abstract: Modern LLM RL systems separate rollout generation from policy optimization. These two stages are expected to produce token probabilities that match ex

safetyarxiv-cs-ai

PreFT: Prefill-only finetuning for efficient inference

model-releasesarxiv-cs-ai

arXiv:2605.14217v1 Announce Type: cross Abstract: Large language models can now be personalised efficiently at scale using parameter efficient finetuning methods (PEFTs), but serving user-specific PEF

Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization

arXiv:2602.05285v2 Announce Type: replace Abstract: A core challenge in structural biophysics is generating biomolecular conformations that are both physically plausible and consistent with experiment

MIDST Challenge at SaTML 2025: Membership Inference over Diffusion-models-based Synthetic Tabular data

arXiv:2603.19185v2 Announce Type: replace Abstract: Synthetic data is often perceived as a silver-bullet solution to data anonymization and privacy-preserving data publishing. Drawn from generative mo