Search: “inference”

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking

arXiv:2605.12995v1 Announce Type: new Abstract: Traditional retrieval pipelines optimize utility through stages of candidate retrieval and reranking, where ranking operates over a predefined candidate

safetyarxiv-cs-lg

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FrameSkip: Learning from Fewer but More Informative Frames in VLA Training

DGX agent

arXiv:2605.13757v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly trained from dense robot demonstration trajectories, often collected through teleoperation, by sampli

safetyarxiv-cs-ro

14 May 2026

GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models

arXiv:2605.13375v1 Announce Type: cross Abstract: In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware

local-aiarxiv-cs-ai

Hierarchical Transformer Preconditioning for Interactive Physics Simulation

model-releasesarxiv-cs-lg

arXiv:2605.13343v1 Announce Type: cross Abstract: Neural preconditioners for real-time physics simulation offer promising data-driven priors, but they often fail to capture long-range couplings effici

Human face perception reflects inverse-generative and naturalistic discriminative objectives

arXiv:2605.12619v1 Announce Type: cross Abstract: The perceptual representations supporting our ability to recognize faces remain a computational mystery. Deep neural networks offer mechanistic hypoth

Information as Maximum-Caliber Deviation: A bridge between Integrated Information Theory and the Free Energy Principle

arXiv:2605.12536v1 Announce Type: cross Abstract: The Free Energy Principle (FEP) is a leading framework for mathematically modeling self-organization and learning, while Integrated Information Theory

interwhen: A Generalizable Framework for Steering Reasoning Models with Test-time Verification

arXiv:2602.11202v3 Announce Type: replace-cross Abstract: Reasoning models produce long traces of intermediate decisions and tool calls, making test-time verification important for ensuring correctnes

Kernel Embeddings and the Separation of Measure Phenomenon

arXiv:2505.04613v4 Announce Type: replace-cross Abstract: We prove that kernel covariance embeddings lead to information-theoretically perfect separation of distinct continuous probability distributio

local-aiarxiv-cs-lg

Latent-Augmented Discrete Diffusion Models

arXiv:2510.18114v3 Announce Type: replace-cross Abstract: Discrete diffusion models have emerged as a powerful class of models and a promising route to fast language generation, but practical implemen

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs

arXiv:2605.12714v1 Announce Type: new Abstract: Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We prop

local-aiarxiv-cs-lg

Learning to Optimize Radiotherapy Plans via Fluence Maps Diffusion Model Generation and LSTM-based Optimization

arXiv:2605.13713v1 Announce Type: new Abstract: Volumetric Modulated Arc Therapy (VMAT) is a cornerstone of modern radiation therapy, enabling highly conformal tumor irradiation and healthy-tissue spa

Local Inverse Geometry Can Be Amortized

arXiv:2605.13068v1 Announce Type: new Abstract: Nonlinear inverse problems often trade inexpensive but fragile first-order updates against curvature-aware methods such as Gauss-Newton and Levenberg-Ma

local-aiarxiv-cs-lg

MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning

arXiv:2605.13037v1 Announce Type: new Abstract: Current interactive LLM agents rely on goal-conditioned stepwise planning, where environmental understanding is acquired reactively during execution rat

Margin-calibrated Classifier Guidance for Property-driven Synthesis Planning

arXiv:2605.13101v1 Announce Type: cross Abstract: Synthesis planning seeks an efficient sequence of chemical reactions that produce a target molecule. Typically, a pretrained single-step (autoregressi

MMSkills: Towards Multimodal Skills for General Visual Agents

arXiv:2605.13527v1 Announce Type: new Abstract: Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as te

Multi-Modal World Model for Physical Robot Interactions: Simultaneous Visual and Tactile Predictions for Enhanced Accuracy

arXiv:2304.11193v2 Announce Type: replace-cross Abstract: Predicting the outcomes of robotic actions, often referred to as learning a world model, in complex environments remains a fundamental challen

Neural Surrogate Forward Modelling For Electrocardiology Without Explicit Intracellular Conductivity Tensor

arXiv:2605.13366v1 Announce Type: new Abstract: Accurate forward modelling is essential for non-invasive cardiac electrophysiology, particularly in atrial fibrillation, where electrical activation is

OCH3R: Object-Centric Holistic 3D Reconstruction

arXiv:2605.13018v1 Announce Type: new Abstract: Object-centric scene understanding is a fundamental challenge in computer vision. Existing approaches often rely on multi-stage pipelines that first app

Pattern-Enhanced RT-DETR for Multi-Class Battery Detection

arXiv:2605.13670v1 Announce Type: new Abstract: Accurate and efficient battery detection is increasingly important for applications in electronic waste recycling, industrial quality control, and autom

Physics-informed neural particle flow for the Bayesian update step

arXiv:2602.23089v2 Announce Type: replace Abstract: The Bayesian update step poses significant computational challenges in high-dimensional nonlinear estimation. While log-homotopy particle flow filte

researcharxiv-cs-lg

Plan for Speed: Dilated Scheduling for Masked Diffusion Language Models

arXiv:2506.19037v4 Announce Type: replace-cross Abstract: Masked diffusion language models (MDLMs) promise fast, non-autoregressive text generation, yet existing samplers, which pick tokens to unmask

PRISM: Prior Rectification and Uncertainty-Aware Structure Modeling for Diffusion-Based Text Image Super-Resolution

arXiv:2605.13027v1 Announce Type: new Abstract: Text image super-resolution (Text-SR) requires more than visually plausible detail synthesis: slight errors in stroke topology may alter character ident

local-aiarxiv-cs-cv

QuickLAP: Quick Language-Action Preference Learning for Semi-Autonomous Systems

arXiv:2511.17855v2 Announce Type: replace Abstract: Robots must learn from both what people do and what they say, but either modality alone is often incomplete: physical corrections are grounded but a

RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records

arXiv:2507.15867v2 Announce Type: replace-cross Abstract: Rare diseases affect 1 in 10 Americans yet remain systematically underdocumented in clinical records. ICD-based systems cannot capture their b

Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning

arXiv:2507.01908v3 Announce Type: replace Abstract: Instruction-based image editing (IIE) has advanced rapidly with the success of diffusion models. However, existing efforts primarily focus on simple

RoSplat: Robust Feed-Forward Pixel-wise Gaussian Splatting for Varying Input Views and High-Resolution Rendering

arXiv:2605.13093v1 Announce Type: new Abstract: Generalizable 3D Gaussian Splatting has recently emerged as an efficient approach for novel-view synthesis, enabling feed-forward synthesis from only a

SECOND-Grasp: Semantic Contact-guided Dexterous Grasping

arXiv:2605.13117v1 Announce Type: cross Abstract: Achieving reliable robotic manipulation, such as dexterous grasping, requires a synergy between physically stable interactions and semantic task guida

Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation

arXiv:2509.21543v3 Announce Type: replace Abstract: Large Language Models (LLMs) have shown strong promise for robotic task planning, particularly through the automatic generation of symbolic planning

researcharxiv-cs-ro

SpurAudio: A Benchmark for Studying Shortcut Learning in Few-Shot Audio Classification

arXiv:2605.13672v1 Announce Type: new Abstract: Few-shot classification (FSC) is widely used for learning from limited labeled data, yet most evaluations implicitly assume that target concepts are ind

Still Camouflage, Moving Illusion: View-Induced Trajectory Manipulation in Autonomous Driving

arXiv:2605.12743v1 Announce Type: cross Abstract: Existing physical adversarial attacks on vision-based autonomous driving induce time-evolving perception errors, including biased object tracking or t

agentsarxiv-cs-cv

StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos

model-releasesarxiv-cs-ai

arXiv:2512.01707v3 Announce Type: replace-cross Abstract: Streaming video understanding requires models not only to process temporally incoming frames, but also to anticipate user intention for realis

Stress-Testing the Reasoning Competence of LLMs With Proofs Under Minimal Formalism

model-releasesarxiv-cs-ai

arXiv:2605.12524v1 Announce Type: cross Abstract: We introduce ProofGrid, a benchmark suite for evaluating LLM reasoning through machine-checkable proofs rather than final answers alone. ProofGrid con

Structural Diversity Drives Disruptive Scientific Innovation

arXiv:2605.12514v1 Announce Type: cross Abstract: Scientific innovation increasingly depends on collaboration, yet the organizational structure that fosters breakthrough ideas remains poorly understoo

safetyarxiv-cs-cv

SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling

arXiv:2602.23013v3 Announce Type: replace Abstract: Detecting visual anomalies in industrial inspection often requires training with only a few normal images per category. Recent few-shot methods achi

Applications

Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks

arXiv:2603.29475v2 Announce Type: replace Abstract: Survival analysis is crucial for many medical applications, but remains challenging for modern machine learning due to limited data, censoring, and

applicationsarxiv-cs-lg

SynCABEL: Synthetic Contextualized Augmentation for Biomedical Entity Linking

model-releasesarxiv-cs-ai

arXiv:2601.19667v2 Announce Type: replace-cross Abstract: We present SynCABEL (Synthetic Contextualized Augmentation for Biomedical Entity Linking), a framework that addresses a central bottleneck in

Test-time Offline Reinforcement Learning on Goal-related Experience

arXiv:2507.18809v2 Announce Type: replace Abstract: Foundation models compress a large amount of information in a single, large neural network, which can then be queried for individual tasks. There ar

safetyarxiv-cs-lg

The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm

model-releasesarxiv-cs-lg

arXiv:2507.18553v4 Announce Type: replace Abstract: Quantizing the weights of large language models (LLMs) from 16-bit to lower bitwidth is the de facto approach to deploy massive transformers onto mo

Applications

ThermalTap: Passive Application Fingerprinting in VR Headsets via Thermal Side Channels

arXiv:2605.12927v1 Announce Type: cross Abstract: Standalone virtual reality (VR) headsets process highly sensitive personal, professional, and health-related data, yet their susceptibility to non-con

applicationsarxiv-cs-cv

Think Twice, Act Once: Verifier-Guided Action Selection For Embodied Agents

arXiv:2605.12620v1 Announce Type: new Abstract: Building generalist embodied agents capable of solving complex real-world tasks remains a fundamental challenge in AI. Multimodal Large Language Models

Towards a holistic understanding of Selection Bias for Causal Effect Identification

arXiv:2605.13430v1 Announce Type: cross Abstract: Selection bias is pervasive in observational studies. For example, large scale biobanks data can exhibit ``healthy volunteer bias'' when respondents a

VideoSEAL: Mitigating Evidence Misalignment in Agentic Long Video Understanding by Decoupling Answer Authority

arXiv:2605.12571v1 Announce Type: cross Abstract: Long video question answering requires locating sparse, time-scattered visual evidence within highly redundant content. Although current MLLMs perform

VIP-COP: Context Optimization for Tabular Foundation Models

arXiv:2605.12904v1 Announce Type: new Abstract: Tabular foundation models (TFMs) have emerged as a powerful paradigm for in-context learning on structured data, enabling direct prediction on new tabul

researcharxiv-cs-lg

Watermarking Should Be Treated as a Monitoring Primitive

arXiv:2605.13095v1 Announce Type: cross Abstract: Watermarking is widely proposed for provenance, attribution, and safety monitoring in generative models, yet is typically evaluated only under adversa

When to Trust Confidence Thresholding: Calibration Diagnostics for Pseudo-Labelled Regression

arXiv:2605.12780v1 Announce Type: cross Abstract: Calibrated probability outputs of trained classifiers are increasingly used as inputs to downstream regression estimands such as effects, prevalences,

safetyarxiv-cs-lg

Where Does Reasoning Break? Step-Level Hallucination Detection via Hidden-State Transport Geometry

arXiv:2605.13772v1 Announce Type: cross Abstract: Large language models hallucinate during multi-step reasoning, but most existing detectors operate at the trace level: they assign one confidence scor

local-aiarxiv-cs-ai

ZeD-MAP: Bundle Adjustment Guided Zero-Shot Depth Maps for Real-Time Aerial Imaging

arXiv:2604.04667v2 Announce Type: replace Abstract: Real-time depth reconstruction from ultra-high-resolution UAV imagery is essential for time-critical geospatial tasks such as disaster response, yet

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone