Search: “inference”

arXiv:2609.00363v1 Announce Type: new Abstract: Conformance suites for quantized GEMM kernels ask whether two implementations agree within a tolerance. We measure what such a suite can detect. Injecti

hardwarearxiv-cs-lg

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HBQ: Hierarchical Scaling Block Quantization with Hardware-Efficiency-Aware Design for Accurate LLM Inference

DGX agent

arXiv:2609.00450v1 Announce Type: cross Abstract: Block Quantization (BQ) is a promising approach for efficient deployment of large language models (LLMs), enabling low-precision computation with cont

model-releasesarxiv-cs-ai

2 Sept 2026

Membership Inference in Fine-tuned Diffusion Language Models via Token-level Memorization Asymmetry

arXiv:2609.00873v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as an alternative modeling paradigm to autoregressive LMs, offering advantages such as parallel g

researcharxiv-cs-cl

Online simultaneous inference for quantiles via smoothed stochastic gradient descent

arXiv:2505.13299v2 Announce Type: replace-cross Abstract: This paper considers the estimation of quantiles via a smoothed version of the stochastic gradient descent (SGD) algorithm. By smoothing the s

researcharxiv-cs-lg

TimeSteer: Inference-Time Speech Scheduling in Joint Audio-Visual Diffusion Models

arXiv:2609.01277v1 Announce Type: cross Abstract: Although pretrained joint audio-visual diffusion models offer rich control over what to generate, they provide no explicit control over when an uttera

Defending Wearable VLMs Against Private Attribute Inference

arXiv:2608.28691v1 Announce Type: cross Abstract: Wearable VLM pipelines promise continuous multimodal assistance from egocentric visual capture: a user asks a task-driven question about the surroundi

Moving the Mean Toward the Known Good, Not Beyond It: What Inference-Time Interventions and Weight Consolidation Buy in Open-Ended Generation

arXiv:2608.28886v1 Announce Type: cross Abstract: What does a generation loop gain from learning on its own verified successes? In cycles of generate, verify, select and LoRA-consolidate on online bin

applicationsarxiv-cs-ai

Pro-Router: Token-Aware Progressive Model Routing with Adaptive Edge-Cloud Collaboration for Efficient Multimodal LLM Inference

arXiv:2608.28726v1 Announce Type: new Abstract: The remarkable performance of multimodal large language models (MLLMs) comes at the cost of substantial computational overhead, posing significant chall

Tensor Methods for Language Models: From Token Representation to Training, Adaptation, Inference, Compression, and Interpretability

arXiv:2608.30505v1 Announce Type: cross Abstract: Large language models (LLMs) are built from structured high-dimensional objects such as token representations, weights, adaptation updates, caches, an

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

arXiv:2305.19366v3 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets), a class of generative models over discrete and structured sample spaces, have been previously applied to the p

safetyarxiv-cs-lg

31 Aug 2026

Active Diffusion-Based Inference for Ill-Posed Inverse Problems under Incomplete Priors

arXiv:2608.27080v1 Announce Type: cross Abstract: Many scientific and engineering applications require estimating unknown parameters from experimentally observable data -- an inverse problem that is i

28 Aug 2026

Agents

Do LLMs Understand Personality? Rethinking Persona Fidelity Evaluation through Structured Behavioral Inference

arXiv:2608.26674v1 Announce Type: cross Abstract: As large language models are increasingly deployed to simulate diverse human characters, ensuring persona fidelity, defined as the extent to which an

agentsarxiv-cs-ai

28 Aug 2026

Simultaneous inference of environmental and interaction forces in collective dynamics

arXiv:2608.25181v1 Announce Type: new Abstract: Collective dynamics arise in a wide range of physical, biological, and engineering applications. Examples include cell migration, swarm robotics, social

27 Aug 2026

The Shadow Price of Intelligence: Quality Degradation in LLM Inference as a Supply Chain Problem

arXiv:2608.23986v1 Announce Type: cross Abstract: Large language model providers are compute constrained, and their universal response to congestion is to degrade service: route queries to smaller mod

26 Aug 2026

Barycentric Fused Gromov-Wasserstein Balancing for Causal Inference under Multiple Treatments

arXiv:2608.22024v1 Announce Type: cross Abstract: Estimating heterogeneous single and interaction treatment effects from observational data under multiple simultaneous treatments is crucial for decisi

local-aiarxiv-cs-ai

Evaluating Inference-Time Defenses Against Package Hallucination in LLM-Generated Code

arXiv:2608.22652v1 Announce Type: cross Abstract: LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into

researcharxiv-cs-ai

KVBoost: Chunk-Level Key-Value Cache Reuse with Deviation-Guided Recomputation for Efficient Large Language Model Inference

arXiv:2608.21362v1 Announce Type: new Abstract: Transformer-based large language models (LLMs) incur high prefill latency because key-value (KV) tensors must be recomputed for each request. Existing p

NeuroPrefetcher: Storage-Aware Sparse LLM Inference via Delta Prefetching

arXiv:2608.22643v1 Announce Type: cross Abstract: Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches

Agents

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes

arXiv:2506.13583v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) agents often exhibit learning behaviors that are not intuitively interpretable by human observers, which can resul

agentsarxiv-cs-ai

24 Aug 2026

Hardware

Valid Inference with Synthetic Data via Task Exchangeability

arXiv:2606.13629v2 Announce Type: replace-cross Abstract: There is a proliferation of work arguing for the use of synthetic data in scientific research. For example, social scientists are arguing for

hardwarearxiv-cs-ai

24 Aug 2026

From Street View Imagery to Street Quality Indicators: Vision Language Inference for the Suburban 15-minute City

arXiv:2608.20026v1 Announce Type: new Abstract: Streetscape quality has become a central concern in contemporary urban planning, particularly within the framework of the pedestrian-friendly 15-minute

applicationsarxiv-cs-cv

21 Aug 2026

Where Grounding Accuracy Lives on the IoU Curve: Label-Free Inference-Time Boundary Refinement

model-releasesarxiv-cs-cv

arXiv:2608.19553v1 Announce Type: new Abstract: Vision--language models can identify the correct referent while returning an imprecise bounding box. We study whether a frozen direct-answer model can u

21 Aug 2026

Efficient INT8 Inference of Small NLP Models on Server CPUs with PyTorch Native Stack

arXiv:2608.18182v1 Announce Type: new Abstract: Small NLP models, especially BERT-family encoders, remain important in industrial workloads such as classification, ranking, and retrieval even in the e

researcharxiv-cs-cl

20 Aug 2026

Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference

arXiv:2608.18982v1 Announce Type: new Abstract: Bioassay activity prediction is often data-limited because drug-discovery datasets rely on time-consuming and expensive wet-lab experiments for data gen

researcharxiv-cs-lg

20 Aug 2026

Same Facts, Different Updates: Inference Setup Shapes LLM Behavior in Medical Allocation

arXiv:2608.18108v1 Announce Type: cross Abstract: Large language models are being incorporated into sensitive and important decision-making processes across nearly all fields. While prior work studies

20 Aug 2026

Inference-Time Attention Steering for Vision-Language-Action Driving Models

arXiv:2608.17095v1 Announce Type: new Abstract: Vision-language-action (VLA) driving models couple a reasoning stage with a diffusion-based trajectory decoder, but do not give a direct way to redirect

local-aiarxiv-cs-cv

19 Aug 2026

Imagining Recovery: Inference-Time Counterfactual Realignment for Vision-Language-Action Models

arXiv:2608.14822v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have improved the flexibility and generality of robotic manipulation, yet they remain fragile to online disruption

safetyarxiv-cs-cv

18 Aug 2026

Inference-Time Mitigation of Adversarial Political Bias in Large Language Models

arXiv:2608.14629v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become the mainstay for information retrieval and summarization tasks, ensuring that they are always non-partisan and

18 Aug 2026

The Note-Chord-Voice Framework: Structured Source Separation and Causal Inference for EV Charging Data

arXiv:2608.14756v1 Announce Type: cross Abstract: Real-world EV charging data exhibit three interlocking pathologies: hardware fragmentation (network timeouts and billing resets split sessions), physi

safetyarxiv-cs-lg

18 Aug 2026

CutClean: Neural Network Pruning for Privacy-Preserving Inference

arXiv:2608.13773v1 Announce Type: cross Abstract: Neural networks are increasingly deployed in high-stakes applications with growing privacy leakage concerns. We show that this privacy leakage can occ

applicationsarxiv-cs-ai

17 Aug 2026

FlashDrive: Flash Vision-Language-Action Inference for Autonomous Driving

arXiv:2608.12932v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise to bring end-to-end reasoning to autonomous driving, but their computational cost remains far too high for r

14 Aug 2026

Generation as Auxiliary Supervision: Enhancing Visual Understanding at Zero Inference Overhead via Decoupled Embedding Prediction

arXiv:2608.12209v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have achieved remarkable progress, visual understanding and generation are typically treated as divergent

researcharxiv-cs-cv

13 Aug 2026

Probably Approximately Correct Maximum A Posteriori Inference

arXiv:2601.16083v2 Announce Type: replace-cross Abstract: Computing the conditional mode of a distribution, better known as the maximum a posteriori (MAP) assignment, is a fundamental task in probabil

researcharxiv-cs-ai

13 Aug 2026

Redistribution-based Cost Inference Improves Sparse Safe Offline RL

arXiv:2608.12306v1 Announce Type: cross Abstract: Safe offline RL typically assumes access to dense per-step cost annotations, but in practice supervisors provide only trajectory-level stop-feedback:

13 Aug 2026

Weighted Sequential Bayesian Inference for Non-Stationary Linear Contextual Bandits

arXiv:2307.03587v4 Announce Type: replace Abstract: In non-stationary linear contextual bandits, existing efficient algorithms typically rely on the Weighted Regularized Least-Squares (WRLS) estimator

researcharxiv-cs-lg

12 Aug 2026

Mask-aware inference with State-Space Models

arXiv:2603.04568v2 Announce Type: replace Abstract: Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For

applicationsarxiv-cs-cv

11 Aug 2026

Path-dependent Discrete Amortized Inference

arXiv:2608.08644v1 Announce Type: new Abstract: We consider the problem of sampling compositional and discrete objects from a given unnormalized posterior distribution. Notably, recent studies have sh

11 Aug 2026

Newton-Schulz Retraction-Based Inference Enables Hidden Quantum Markov Models to Outperform Classical HMMs

arXiv:2608.06554v1 Announce Type: new Abstract: Hidden Markov models (HMMs) are widely used probabilistic models for discrete sequential data but can be limited when hidden dynamics are complex. Hidde

10 Aug 2026

Dual-space posterior sampling for Bayesian inference in constrained inverse problems

arXiv:2603.00393v2 Announce Type: replace-cross Abstract: Inverse problems constrained by partial differential equations are often ill-conditioned due to noisy, incomplete data or inherent non-uniquen

7 Aug 2026

From Sports to Safety: Benchmarking Proactive Risk Inference in MLLMs

model-releasesarxiv-cs-cl

arXiv:2608.05560v1 Announce Type: cross Abstract: Timely anticipation of physical hazards is essential for real-world safety, yet existing MLLM evaluations focus on harmful content or general risks, l

7 Aug 2026

Interpretable Fuzzy Inference for UAV Target Tracking Using Bounding-Box Geometry

arXiv:2608.04121v1 Announce Type: cross Abstract: Vision-based guidance of unmanned aerial vehicles (UAVs) toward unmanned ground vehicles (UGVs) supports cooperative aerial--ground robotics, but reli

local-aiarxiv-cs-ai

6 Aug 2026

Strengthening Target-Language Features: SAE-Based Steering for Multilingual Inference

model-releasesarxiv-cs-cl

arXiv:2608.04904v1 Announce Type: new Abstract: Multilingual large language models exhibit substantial performance differences across languages, while existing adaptation methods often require paramet

6 Aug 2026

SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery

arXiv:2608.04930v1 Announce Type: cross Abstract: Bayesian causal discovery seeks to determine the posterior distribution of causal theories, which are interpreted as directed acyclic graphs (DAGs) th

researcharxiv-cs-ai

6 Aug 2026

Amortized Inference of Multi-Modal Posteriors using Likelihood-Weighted Normalizing Flows

arXiv:2512.04954v3 Announce Type: replace Abstract: We present a novel technique for amortized posterior estimation using Normalizing Flows trained with likelihood-weighted importance sampling. This a

Beyond Accuracy: Auditing Spatial Provenance in Visual Token Pruning for OCR-Critical MLLM Inference

model-releasesarxiv-cs-cv

arXiv:2608.00077v1 Announce Type: new Abstract: Visual-token pruning is usually judged by answer quality at a fixed retention budget. For text-rich multimodal large language models (MLLMs), this proto

HyperODE: Zero-Shot Surrogate for Simulation and Inference of Dynamical Systems

arXiv:2608.00852v1 Announce Type: new Abstract: Understanding and controlling complex dynamical systems often requires executing thousands of numerical simulations across vast parametric landscapes, w

Mitigating Visual Hallucinations in Multimodal Systems through Retrieval-Augmented Reliability-Aware Inference

arXiv:2606.15782v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have demonstrated strong capabilities in vision-language understanding and natural-language response

safetyarxiv-cs-cv

Uncertainty-Aware Simulation-Based Inference for Operations Research with Large Language Models

arXiv:2608.00019v1 Announce Type: new Abstract: Deploying large language models (LLMs) for operations research (OR) tasks remains challenging because correctness depends on a coherent modeling process

local-aiarxiv-cs-lg