Search: “inference”

Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference

arXiv:2510.09574v2 Announce Type: replace Abstract: Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on

local-aiarxiv-cs-ro

23 Apr 2026

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Structured Disagreement in Health-Literacy Annotation: Epistemic Stability, Conceptual Difficulty, and Agreement-Stratified Inference

DGX agent

arXiv:2604.19943v1 Announce Type: new Abstract: Annotation pipelines in Natural Language Processing (NLP) commonly assume a single latent ground truth per instance and resolve disagreement through lab

applicationsarxiv-cs-cl

23 Apr 2026

Tutorials

Topology-Aware Skeleton Detection via Lighthouse-Guided Structured Inference

arXiv:2604.20123v1 Announce Type: new Abstract: In natural images, object skeletons are used to represent geometric shapes. However, even slight variations in pose or movement can cause noticeable cha

tutorialsarxiv-cs-cv

23 Apr 2026

Agents

X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference

arXiv:2604.20289v1 Announce Type: new Abstract: Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Rec

agentsarxiv-cs-cv

23 Apr 2026

Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention

arXiv:2604.19530v1 Announce Type: new Abstract: Transformer-based scientific foundation models are increasingly deployed in high-stakes settings, but current architectures give deterministic outputs a

22 Apr 2026

CounterRefine: Answer-Conditioned Counterevidence Retrieval for Inference-Time Knowledge Repair in Factual Question Answering

arXiv:2603.16091v2 Announce Type: replace-cross Abstract: In factual question answering, many errors are not failures of access but failures of commitment: the system retrieves relevant evidence, yet

22 Apr 2026

Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps

arXiv:2604.19565v1 Announce Type: cross Abstract: Hallucinations in Speech Large Language Models (SpeechLLMs) pose significant risks, yet existing detection methods typically rely on gold-standard out

22 Apr 2026

Generalization Boundaries of Fine-Tuned Small Language Models for Graph Structural Inference

arXiv:2604.18092v1 Announce Type: new Abstract: Small language models fine-tuned for graph property estimation have demonstrated strong in-distribution performance, yet their generalization capabiliti

Tutorials

Learning Invariant Modality Representation for Robust Multimodal Learning from a Causal Inference Perspective

arXiv:2604.18460v1 Announce Type: new Abstract: Multimodal affective computing aims to predict humans' sentiment, emotion, intention, and opinion using language, acoustic, and visual modalities. Howev

tutorialsarxiv-cs-lg

Safe Control using Learned Safety Filters and Adaptive Conformal Inference

arXiv:2604.18482v1 Announce Type: cross Abstract: Safety filters have been shown to be effective tools to ensure the safety of control systems with unsafe nominal policies. To address scalability chal

Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles

arXiv:2604.17156v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a promising framework for solving inverse problems governed by partial differential equations (

researcharxiv-cs-lg

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models

arXiv:2604.14156v1 Announce Type: new Abstract: Large language models deliver strong generative performance but at the cost of massive parameter counts, memory use, and decoding latency. Prior work ha

17 Apr 2026

Hardware

Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3

arXiv:2603.27844v2 Announce Type: replace Abstract: Majority voting over multiple LLM attempts improves mathematical reasoning, but correlated errors limit the effective sample size. A natural fix is

hardwarearxiv-cs-cl

17 Apr 2026

POP: Prefill-Only Pruning for Efficient Large Model Inference

arXiv:2602.03295v2 Announce Type: replace Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated remarkable capabilities. However, their deployment is hindered by s

17 Apr 2026

Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference

arXiv:2604.13252v1 Announce Type: new Abstract: Anomaly detection aims to identify observations that deviate from expected behavior. Because anomalous events are inherently sparse, most frameworks are

16 Apr 2026

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference

arXiv:2512.15742v2 Announce Type: replace Abstract: Pre-trained Vision Kolmogorov-Arnold Networks (KANs) store a dense B-spline grid on every edge, inflating prediction-head parameter counts by more t

16 Apr 2026

TRIM: Hybrid Inference via Targeted Stepwise Routing in Multi-Step Reasoning Tasks

arXiv:2601.10245v2 Announce Type: replace-cross Abstract: Multi-step reasoning tasks like mathematical problem solving are vulnerable to cascading failures, where a single incorrect step leads to comp

safetyarxiv-cs-cl

16 Apr 2026

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference

arXiv:2604.12913v1 Announce Type: cross Abstract: Binary decompilation is a critical reverse engineering task aimed at reconstructing high-level source code from stripped executables. Although Large L

15 Apr 2026

A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs

arXiv:2604.09752v1 Announce Type: cross Abstract: During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces seve

researcharxiv-cs-ai

Active Bayesian Inference for Robust Control under Sensor False Data Injection Attacks

arXiv:2604.11410v1 Announce Type: new Abstract: We present a framework for bridging the gap between sensor attack detection and recovery in cyber-physical systems. The proposed framework models modern

researcharxiv-cs-lg

Active Inference with a Self-Prior in the Mirror-Mark Task

arXiv:2604.09673v1 Announce Type: cross Abstract: The mirror self-recognition test evaluates whether a subject touches a mark on its own body that is visible only in a mirror, and is widely used as an

researcharxiv-cs-ai

CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration

arXiv:2509.17458v3 Announce Type: replace-cross Abstract: Text-to-image diffusion models, such as Stable Diffusion, can produce high-quality and diverse images but often fail to achieve compositional

Prompt Relay: Inference-Time Temporal Control for Multi-Event Video Generation

arXiv:2604.10030v1 Announce Type: new Abstract: Video diffusion models have achieved remarkable progress in generating high-quality videos. However, these models struggle to represent the temporal suc

safetyarxiv-cs-cv

Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference

arXiv:2604.09613v1 Announce Type: cross Abstract: Production vLLM fleets provision every instance for worst-case context length, wasting 4-8x concurrency on the 80-95% of requests that are short and s

Adaptive Action Chunking at Inference-time for Vision-Language-Action Models

arXiv:2604.04161v2 Announce Type: replace Abstract: In Vision-Language-Action (VLA) models, action chunking (i.e., executing a sequence of actions without intermediate replanning) is a key technique t

applicationsarxiv-cs-ro

13 Apr 2026

Hidden in Plain Sight: Visual-to-Symbolic Analytical Solution Inference from Field Visualizations

arXiv:2604.08863v1 Announce Type: new Abstract: Recovering analytical solutions of physical fields from visual observations is a fundamental yet underexplored capability for AI-assisted scientific rea

13 Apr 2026

Hardware

High-dimensional inference for the gamma-ray sky with differentiable programming

arXiv:2604.08648v1 Announce Type: cross Abstract: We motivate the use of differentiable probabilistic programming techniques in order to account for the large model-space inherent to astrophysical gam

hardwarearxiv-cs-lg

13 Apr 2026

Clickbait detection: quick inference with maximum impact

arXiv:2604.08148v1 Announce Type: new Abstract: We propose a lightweight hybrid approach to clickbait detection that combines OpenAI semantic embeddings with six compact heuristic features capturing s

researcharxiv-cs-cl

10 Apr 2026

MARCH: Evaluating the Intersection of Ambiguity Interpretation and Multi-hop Inference

arXiv:2509.22750v3 Announce Type: replace Abstract: Real-world multi-hop QA is naturally linked with ambiguity, where a single query can trigger multiple reasoning paths that require independent resol

10 Apr 2026

The End of the Foundation Model Era: Open-Weight Models, Sovereign AI, and Inference as Infrastructure

arXiv:2604.06217v1 Announce Type: cross Abstract: The foundation model era -- roughly 2020 to 2025 -- is over. The forces that defined it have inverted. Open source models have reached frontier perfor

safetyarxiv-cs-ai

10 Apr 2026

AI Knows Where You Are: Exposure, Bias, and Inference in Multimodal Geolocation with KoreaGEO

model-releasesarxiv-cs-cv

arXiv:2506.03371v2 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have enabled accurate image-based geolocation, raising serious concerns about location privacy risk

16 Oct 2026

MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Vision

model-releasesarxiv-cs-cv

arXiv:2610.12568v2 Announce Type: replace Abstract: Feed-forward 3D priors enable high-quality reconstruction from image streams but often lack reliable metric scale and suffer from long-term trajecto

PLACID: Privacy-preserving Large language models for Acronym Clinical Inference and Disambiguation

arXiv:2603.23678v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy const

Taking the PULSE of Medical Reasoning: Step-Level Retrieval Timing for Knowledge-Grounded Inference

arXiv:2610.20292v1 Announce Type: new Abstract: Reliable medical reasoning requires LLMs to dynamically access external biomedical evidence to improve factual trustworthiness and reasoning accuracy. H

applicationsarxiv-cs-cl

When Does Depth Help? Understanding Layerwise Inference in Tabular Foundation Models

arXiv:2610.19814v1 Announce Type: new Abstract: Transformer-based tabular foundation models (TFMs) achieve state-of-the-art performance on small to medium-sized tabular prediction tasks while processi

local-aiarxiv-cs-lg

Inference on the Value of Policy Improvement in Adaptive Experiments

arXiv:2610.15789v1 Announce Type: cross Abstract: In this paper, we develop an asymptotically normal estimator for the value of policy improvement (VPI) under adaptively collected data. This value, wh

safetyarxiv-cs-lg

14 Oct 2026

ViewStruct: View-Grounded Articulation and Connectivity Inference

arXiv:2610.16793v1 Announce Type: new Abstract: Interacting with unfamiliar objects requires understanding how their parts connect and move. We introduce ViewStruct, a framework for jointly predicting

applicationsarxiv-cs-cv

14 Oct 2026

zip2zip++: Towards Inference-Time Token Compression with Minimal Quality Loss

arXiv:2610.13605v1 Announce Type: new Abstract: Dynamic vocabularies built on-the-fly via Lempel-Ziv-Welch (LZW) compression let a language model represent the same text in fewer tokens, but prior wor

researcharxiv-cs-cl

12 Oct 2026

Class Machine Unlearning for Complex Data via Concepts Inference and Data Poisoning

arXiv:2405.15662v2 Announce Type: replace Abstract: Machine unlearning aims to remove the influence of specified training data or knowledge from a trained model without requiring full retraining. This

local-aiarxiv-cs-lg

9 Oct 2026

When Has a Bayesian Neural Network Sampled Enough? Adaptive Inference Time with Statistical Guarantees

arXiv:2610.12212v1 Announce Type: new Abstract: Bayesian neural network predictions are commonly approximated using a fixed number of Monte Carlo samples per input, without controlling the resulting e

researcharxiv-cs-ai

9 Oct 2026

Possibilistic Radial Transport for Approximate IM Inference

arXiv:2610.09956v1 Announce Type: cross Abstract: Probing the hypothesis space after seeing the data remains valid under possibilistic inferential models (IMs), provided the significance level stays f

8 Oct 2026

LBA-CBF: Rapidly Adaptive Safety Filters via Parallel Dynamics Inference

arXiv:2610.08765v1 Announce Type: new Abstract: Control barrier functions (CBFs) certify commands through an assumed dynamics model, so an abrupt, unmeasured regime change can undermine the certificat

safetyarxiv-cs-ro

7 Oct 2026

A Statistical Inference Framework for PMI Estimation and SGNS Word Embeddings

arXiv:2610.05058v1 Announce Type: cross Abstract: Pointwise Mutual Information (PMI) is a core measure of testing word association, and Skip-gram with Negative Sampling (SGNS) is essentially a method

safetyarxiv-cs-lg

6 Oct 2026

Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation

arXiv:2610.00793v1 Announce Type: cross Abstract: We consider the estimation of drift, diffusion, and noise covariance from discrete observations of stochastic differential equations driven by Gaussia

researcharxiv-cs-lg

2 Oct 2026

Not All Error Yields to Scale: Where Scaling Stops in Vision-Language Inference

arXiv:2610.01640v1 Announce Type: cross Abstract: Vision-language models (VLMs) face a fixed-budget trade-off between processing more visual information for fine-grained perception and using a larger

applicationsarxiv-cs-ai

2 Oct 2026

Beyond Token Importance: Preserving Spatial Scaffolds for Efficient Vision-Language-Action Inference

arXiv:2609.36967v1 Announce Type: new Abstract: Existing VLA pruning strategies primarily select individual visual tokens according to task-level semantic relevance, while overlooking the spatial info

researcharxiv-cs-ro

30 Sept 2026

CHAIN: Calibrated LLM Forecasting via Causal-Temporal Hypergraph Inference

arXiv:2609.36689v1 Announce Type: cross Abstract: Large language models have achieved significant progress in event forecasting, yet their probability outputs exhibit systematic calibration bias that

safetyarxiv-cs-cl

30 Sept 2026

HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment