Search: “inference”

arXiv:2610.11959v1 Announce Type: new Abstract: Reinforcement learning (RL) is the central training paradigm for advancing large foundation models towards self-improvement. This report introduces the

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MotiveMob: Motivation as Semantic Action for Closed-Loop Human Mobility Generation

DGX agent

arXiv:2610.11442v1 Announce Type: new Abstract: Human mobility generation, an important task in urban research, synthesizes trajectory data for urban planning and transportation management. Human mobi

researcharxiv-cs-lg

9 Oct 2026

MRCert: Towards Post-deployment Patch Robustness Certification for Adversarially Patched Samples via Type-specific Masking

arXiv:2610.10617v1 Announce Type: cross Abstract: In post-deployment time, inputs to deep learning models may or may not be adversarially patched. Patch robustness certification on such inputs within

researcharxiv-cs-ai

Omni-Diffusion-Distill: Few-Step Distillation of Unified Multimodal Diffusion Large Language Models

arXiv:2610.10990v1 Announce Type: new Abstract: Unified multimodal diffusion large language models (dLLMs) offer a single architecture for both image generation and multimodal understanding, but their

tutorialsarxiv-cs-cv

One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts

model-releasesarxiv-cs-cv

arXiv:2610.12448v1 Announce Type: new Abstract: In this work, we show that a single Transformer block, applied recurrently, can match the accuracy of a full-depth vision encoder at comparable inferenc

OuroWorld: Bringing Any 3D World Alive as Diverse, Endlessly Looping 3D Cinemagraphs

arXiv:2610.12461v1 Announce Type: new Abstract: Recent 3D world models generate photorealistic, explorable scenes that remain frozen in time. OuroWorld is a mask-free framework that turns any static 3

tutorialsarxiv-cs-cv

Parametric Trajectory Distillation for Few-Step Video Generation

arXiv:2610.11498v1 Announce Type: new Abstract: Video diffusion and flow models require many sequential evaluations, making generation computationally expensive. Few-step distillation reduces this cos

tutorialsarxiv-cs-cv

Phonological Interference in Multilingual Speech Models

arXiv:2610.11275v1 Announce Type: new Abstract: Phoneme-level models transcribe or generate speech as a sequence of phonemes, the smallest sound units that distinguish words. These models enable fine-

local-aiarxiv-cs-cl

PLaW-VLA: Predictive Latent World Modeling for Vision-Language-Action Policies

arXiv:2610.12285v1 Announce Type: new Abstract: Learning to predict how the world evolves can provide vision-language-action (VLA) policies with predictive context for long-horizon control, but its ef

safetyarxiv-cs-ro

PMTRM: Pseudo-Memory Temporal Re-encoding Module for Embodied Policy Learning

arXiv:2610.11168v1 Announce Type: cross Abstract: Robotic manipulation often contains repeated motions whose local observations look similar at different phases. When these phases require different ac

local-aiarxiv-cs-ai

Pose-Free Feed-Forward 3D Inpainting via Learnable Mask Attention and Support Token Refinement

arXiv:2610.11857v1 Announce Type: new Abstract: 3D scene inpainting aims to recover missing or occluded regions in edited 3D scenes, while ensuring geometric and textural consistency. Existing approac

Puffin: Probabilistic Learning of Spatial Detail From Coarse Observations

arXiv:2610.11914v1 Announce Type: new Abstract: High-resolution socioeconomic variables are important for applications such as urban planning, public health, disaster response, and resource allocation

Ranking Prior Alignment for Credit Risk Modeling: When Do External Priors Matter?

arXiv:2610.11146v1 Announce Type: new Abstract: Cold-start credit scoring -- deploying models with scarce labeled data, weak features, or minimal capacity -- is a recurring problem in financial machin

Reading the Room: Foundations, Design, and Challenges of Normative Competence in LLMs

arXiv:2610.10906v1 Announce Type: new Abstract: Human communities are governed by normative systems: shared standards that produce extit{norms} dictating acceptable behavior, enforced through communit

safetyarxiv-cs-ai

Reconstruction of Multiscale Plasma Dynamics Across Operating Regimes

arXiv:2610.11004v1 Announce Type: cross Abstract: Reconstructing spatially resolved plasma dynamics from few sensors is essential for diagnostics, reduced-order modelling and control, yet remains diff

Residual Modeling Closes the Regression and Generative Policy Gap in Robot Learning

arXiv:2610.12231v1 Announce Type: new Abstract: Learning from demonstration has enabled impressive robot behaviors. A common choice for policy learning is to use diffusion or flow matching (Flow-Polic

safetyarxiv-cs-ro

ReTeach: Building a Self-Teacher through Multi-Round Reflection and Retry

arXiv:2610.11529v1 Announce Type: new Abstract: Self-distillation can improve reasoning without a separately trained, more capable teacher, but its effectiveness depends on how the self-teacher gains

safetyarxiv-cs-ai

Rethinking Contrastive Loss in CLIP Post-training: A Complementary Framework with Frozen Text Encoder

arXiv:2610.11374v1 Announce Type: cross Abstract: CLIP serves as a foundational vision-language model and the de facto vision encoder for downstream VLMs such as LLaVA. Post-training offers a lightwei

researcharxiv-cs-ai

S^3Geo: Structure-Semantic Synergistic Learning for Cross-View Geo-Localization

arXiv:2610.11608v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) aims to estimate geographic locations by matching images captured from different viewpoints, such as drone and satell

local-aiarxiv-cs-cv

SACQ: Structured Decoding with Memory-Conditioned Refinement for Long-Horizon Forecasting

arXiv:2610.11170v1 Announce Type: new Abstract: Long-term time series forecasting (LTSF) models predominantly employ patch-based encoders terminated by a flatten readout head that maps the entire enco

safetyarxiv-cs-lg

SatFix: Absolute Visual Localization of UAVs in Satellite Maps from a Single Oblique Image

arXiv:2610.11049v1 Announce Type: new Abstract: We study absolute metric UAV localization within a provided geo-referenced satellite region, recovering continuous map position and viewing heading from

local-aiarxiv-cs-cv

SDPAD: A Fully Spike-Driven Pipeline for End-to-End Autonomous Driving

arXiv:2610.11583v1 Announce Type: cross Abstract: End-to-end autonomous driving demands trajectory planners that are both highly accurate and cheap enough for edge deployment. State-of-the-art artific

Seek-and-View Reasoning for Multi-View Spatial Understanding

arXiv:2610.11810v1 Announce Type: new Abstract: Existing approaches to multi-view spatial reasoning operate largely on sparse input views. Vision-language models (VLMs) are thus restricted to understa

safetyarxiv-cs-cv

Selective Listening: Mechanism-Guided Control of Audio Influence in Large Audio-Language Models

arXiv:2610.11196v1 Announce Type: cross Abstract: Large audio-language models (LALMs) exploit multimodal evidence, yet task-irrelevant audio can alter text-reasoning decisions when listening is unnece

researcharxiv-cs-cl

Smoothing the Top-k Exposure Boundary for Sparse Mixture-of-Experts

model-releasesarxiv-cs-cl

arXiv:2610.11575v1 Announce Type: new Abstract: Sparse Mixture-of-Experts models scale parameter capacity efficiently while maintaining a fixed compute budget per token. However, traditional training

SpatialOPSD: Self-Distilling Spatial Intelligence from Verified Coding Agent Traces

arXiv:2610.11366v1 Announce Type: new Abstract: Spatial coding agents significantly improve spatial reasoning in Multimodal Large Language Models (MLLMs) by using external tools to generate verified e

safetyarxiv-cs-lg

Spectral Weight Decay: Inducing Low-Rank Structure in Neural Network Weights

arXiv:2610.11730v1 Announce Type: new Abstract: Standard weight decay treats each weight matrix as a vector and ignores its spectral structure. We introduce spectral weight decay, a post-step decouple

SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting

arXiv:2610.11229v1 Announce Type: new Abstract: Time series forecasting aims to predict future values from historical observations and auxiliary features. We propose extbf{SteerCast}, a retrieval-base

Streaming-Aware Diffusion for Real-Time Video Super-Resolution via Cross-Step Attention

arXiv:2610.11746v1 Announce Type: new Abstract: Real-time video super-resolution requires high spatio-temporal fidelity under strict latency constraints, challenging diffusion models due to their iter

Test-Time Compute for Tabular Foundation Models: Mechanisms, Gains, and Limits

arXiv:2610.12005v1 Announce Type: new Abstract: Which forms of test-time compute improve the predictions of strong pretrained tabular foundation models (TFMs)? We systematically study this along three

The Polytopal Neural Network

arXiv:2610.12004v1 Announce Type: cross Abstract: Understanding how deep neural networks process information remains a central challenge. Existing interpretability methods often compromise structural

safetyarxiv-cs-ai

Applications

UniData: Universal Multimodal Instruction Generation Pipeline

arXiv:2610.11363v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly being applied in a wider range of real-world scenarios. However, due to the substantial labor

applicationsarxiv-cs-ai

USDCraft: Geometrically Grounded Programmatic Modeling of Articulated 3D Assets for Simulation

arXiv:2610.11322v1 Announce Type: new Abstract: Geometrically faithful and functional articulated 3D assets are essential for real-to-sim robot manipulation, where policies trained in simulation must

tutorialsarxiv-cs-ro

Using LMs to Model the Effects of Context and Coreference during Sentence Comprehension

model-releasesarxiv-cs-cl

arXiv:2609.32119v2 Announce Type: replace Abstract: Language models (LMs) are often used as a tool to model human language processing. Recent studies suggest that severely restricting LMs' context win

Visible Reasoning Is Not a Universal Optimizer: Persona- and Thinking-Dependent Effects in Analytics Code Generation

arXiv:2610.10639v1 Announce Type: cross Abstract: Visible Chain-of-Thought (CoT) is often treated as a broadly useful reasoning instruction, yet analytics code generation combines natural-language amb

ViSkill: Reinforcing VLM Agents with Evolving Visual-Native Skills

arXiv:2610.12403v1 Announce Type: cross Abstract: Skill-augmented agents improve sample efficiency by distilling successful trajectories into reusable strategies. Yet most existing approaches remain t

safetyarxiv-cs-cl

WAND: Learning Robust Navigation under Complex Wind Disturbances and Dense Obstacles for Quadrotors

arXiv:2610.11809v1 Announce Type: new Abstract: Robust navigation in cluttered environments remains a fundamental challenge for quadrotors, particularly when strong wind disturbances arise, which pert

safetyarxiv-cs-ro

What to Admit and How to Present: Governing Persistent Memory in LLM Agents

arXiv:2610.11188v1 Announce Type: new Abstract: Persistent memory can improve personalization in LLM agents but can also induce sycophancy and cross-domain leakage. We distinguish two governance decis

When Citations Mislead? A Claim-Level Benchmark for Legal Hallucination Detection

arXiv:2610.10971v1 Announce Type: cross Abstract: Large language models are increasingly used in legal research and drafting, but they can still produce claims that sound convincing without being supp

Where Draft Trees Lose Target Mass: Exit-Guided Speculative Decoding

arXiv:2610.11750v1 Announce Type: new Abstract: Tree-based speculative decoding verifies multiple draft continuations in one target-model pass, but finite trees built from draft scores face a fundamen

researcharxiv-cs-ai

A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding

arXiv:2610.08792v1 Announce Type: new Abstract: We present a foundational formulation of the Bayesian Mirror Architecture (BMA), a self-referential generative framework in which sensory abstractions,

tutorialsarxiv-cs-lg

A Self-Pruning Transformer: Extreme KV-Cache Compression with Universal Attention

arXiv:2610.09051v1 Announce Type: new Abstract: The large KV-cache size of modern LLMs creates a barrier to efficient deployment. Recent work has explored replacing attention layers' RoPE positional e

A Vehicle-Integrated Approach to Digital Twin Deployment for Bridges Through Drive-By Sensing

arXiv:2610.08822v1 Announce Type: new Abstract: Ageing bridge infrastructure is a growing global concern, yet conventional Structural Health Monitoring (SHM) systems are costly and difficult to scale,

Adaptive Visual Token Reduction for Accelerated Image Understanding

arXiv:2610.09252v1 Announce Type: new Abstract: Large Vision-Language Models achieve strong VQA performance, but processing high-resolution, information-rich images requires substantial computation, m

Adversarial Images Hijack Web Agents from Visual Grounding to Browser Execution

model-releasesarxiv-cs-cl

arXiv:2610.09240v1 Announce Type: cross Abstract: Modern web agents built on large vision-language models process webpages, select relevant UI elements, and translate model outputs into browser action

Attention via Black-Box Vector Search

arXiv:2610.10135v1 Announce Type: cross Abstract: Sparse attention mechanisms estimate attention over n tokens using a small subset of keys. Many existing approaches use maximum inner product search (

Bounded Autonomy and Verifiable Safety for Agentic AI Enabled Automation

arXiv:2610.08815v1 Announce Type: new Abstract: Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drif

Bringing BNNs to Fast Event Processing

arXiv:2610.09873v1 Announce Type: new Abstract: Binary Neural Networks (BNNs) enable efficient deep learning deployment on resource constrained devices with weights and activations compressed to one b