Search: “framework”

Semi-Supervised Learning under Spatially Biased Sampling

arXiv:2609.07982v1 Announce Type: new Abstract: Standard semi-supervised learning (SSL) typically relies on labelled and unlabelled data sharing a common marginal distribution. This assumption is ofte

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SHIFT: Surface-aware High-speed Integration For TSDFs

DGX agent

arXiv:2609.06547v1 Announce Type: new Abstract: Real-time 3D mapping is fundamental for autonomous robotic navigation, with Euclidean Signed Distance Fields (ESDFs) serving as the standard representat

agentsarxiv-cs-ro

9 Sept 2026

SkillX: Unified Multi-Skill Policy Learning for Humanoid Soccer

arXiv:2609.06718v1 Announce Type: new Abstract: Humanoid soccer is a challenging testbed for dynamic whole-body control, requiring robots to coordinate balance, locomotion, object interaction, and ski

safetyarxiv-cs-ro

Smoothed Picard Hamiltonian Monte Carlo

arXiv:2609.06906v1 Announce Type: cross Abstract: We develop a new low-accuracy sampler, called smoothed Picard Hamiltonian Monte Carlo, which combines Gaussian smoothing, Picard iteration, and higher

Local Ai

Solution for UCF UrbanTwin V2X-Real Track: Sim-to-Real Urban LiDAR 3D Object Detection

arXiv:2609.07608v1 Announce Type: new Abstract: Bridging the simulation-to-reality gap in roadside LiDAR requires addressing several coupled discrepancies, including scene geometry, sampling density,

local-aiarxiv-cs-cv

Spectral Prioritized Sweeping in Nonstationary Reinforcement Learning

arXiv:2609.06186v1 Announce Type: new Abstract: Prioritized Sweeping (PS) accelerates model-based reinforcement learning by selecting backups according to Bellman residual magnitude. In nonstationary

Speed Limit for Information Acquisition in Stochastic Learning Dynamics

arXiv:2609.08219v1 Announce Type: cross Abstract: Neural networks acquire internal representations through learning. In this work, we formulate stochastic gradient descent (SGD) as a Markovian stochas

SphereSOD: Geometry-Structure Coupled Learning for 360 Salient Object Detection

arXiv:2609.07571v1 Announce Type: new Abstract: 360{eg} salient object detection (SOD) aims to accurately segment salient regions across a full field of view. However, equirectangular projection (ERP)

Spheriverse: 3D Scene Understanding from Spherical Observations in the Wild

arXiv:2609.09012v1 Announce Type: new Abstract: Spherical observations provide global visual context for 3D scene understanding. However, visual information is encoded in an angular domain, whereas th

SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions

arXiv:2510.08999v2 Announce Type: replace Abstract: Compressing large-scale neural networks is essential for deploying models on resource-constrained devices. Most existing methods adopt weight prunin

Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method

arXiv:2507.18073v2 Announce Type: replace Abstract: Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can s

Stable-MM-R1: Anchoring Multimodal Reasoning Dynamics via Entropy-Guided Stratification

arXiv:2609.07148v1 Announce Type: cross Abstract: While Reinforcement Learning (RL) effectively incentivizes reasoning in Large Language Models, current pipelines are hindered by training instability

STAR-Pro: Stage-Wise Token Adaptive Reduction with Progressive Refinement for Efficient Large Vision-Language Models

arXiv:2609.05916v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal understanding, but the hundreds to thousands of visual tokens they process impose substan

Steering Geometry: Validating Human Value Geometry in LLM Steering Space

arXiv:2609.06289v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in alignment-sensitive contexts, activation steering has emerged as a lightweight, inference

Steering Under Compression: Dose-Response, Capability Cost, and Failure Asymmetry in Quantized LLMs

arXiv:2609.06473v1 Announce Type: new Abstract: Inference-time activation steering enables behavioral control of large language models without parameter modification, while post-training quantization

STSG-VQA: Evidence-Grounded Temporal Question Answering from Surgical Spatio-Temporal Scene Graphs

arXiv:2609.08543v1 Announce Type: new Abstract: Despite recent advances in surgical vision-language models (VLMs), temporal reasoning remains limited because existing supervision is largely frame-cent

Sub-Pixel Affine Registration of Space Debris Images via the Radon Point Spread Function

arXiv:2609.06929v1 Announce Type: new Abstract: Inter-frame affine misalignment caused by platform jitter and attitude adjustments poses a fundamental challenge for multi-frame analysis of point targe

Subject-Relative Micro-Motion and Sleep Dynamics for Near-Infrared Video Sleep Staging

arXiv:2609.05550v1 Announce Type: new Abstract: Near-infrared (NIR) video is a promising modality for contactless sleep monitoring, but recent video-based sleep staging methods often use it as a route

Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation

arXiv:2603.28678v2 Announce Type: replace Abstract: We introduce PACE, a backpropagation-free continual test-time adaptation system that directly optimizes the affine parameters of normalization layer

SUN: Reaching for Novelty in Reinforcement Learning

arXiv:2609.08642v1 Announce Type: new Abstract: Exploration in reinforcement learning (RL) remains a fundamental challenge. Recent goal-conditioned RL strategies (which select goals to encourage broad

Supervised Cross-Modal Feature Alignment for Zero-Wearable Freezing of Gait Detection in Parkinsonism

arXiv:2609.08317v1 Announce Type: new Abstract: Objective assessment of Freezing of Gait (FoG) in Parkinson's disease (PD) relies predominantly on wearable Inertial Measurement Units (IMUs). While IMU

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories

arXiv:2601.13713v2 Announce Type: replace-cross Abstract: Software testing is crucial for ensuring the correctness and reliability of software systems. Automated generation of issue reproduction tests

applicationsarxiv-cs-lg

Synthesizability Prediction of Crystalline Structures with Structure-Aware Feature Learning and Uncertainty Quantification

arXiv:2510.19251v2 Announce Type: replace-cross Abstract: Predicting which hypothetical inorganic crystals can be experimentally realized remains a central challenge in accelerating materials discover

TabBench-Bio: A Living Benchmark for Machine Learning on High-Dimensional Biomedical Tables

arXiv:2609.07441v1 Announce Type: new Abstract: Biomedical tables often combine thousands of measured variables with only tens or hundreds of labelled samples, a regime that is poorly represented in g

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

arXiv:2609.09158v1 Announce Type: new Abstract: We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that model navigation as a 2D path p

applicationsarxiv-cs-ro

Tutorials

TeMo: Temperature Modulation for Multimodal Contrastive Learning

arXiv:2609.07540v1 Announce Type: new Abstract: Contrastive learning approaches achieve strong performance by training models to bring similar samples closer while pushing dissimilar samples apart. A

tutorialsarxiv-cs-cv

Temporal-Causal Inference for Reinforcement Learning via Automata Learning

arXiv:2609.07461v1 Announce Type: new Abstract: We consider reinforcement learning in environments with dynamics that undergo an irreversible phase transition governed by a hidden temporal pattern. Th

Tensor network representations of discrete maximum entropy distributions via mean polytopes

arXiv:2609.07184v1 Announce Type: cross Abstract: We present tensor network representations for discrete maximum entropy distributions under expectation constraints. To this end, we introduce Computat

applicationsarxiv-cs-lg

The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation

arXiv:2609.08901v1 Announce Type: new Abstract: Approximate machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. We identify

The case for boycotting Generative AI: https://garymarcus.substack.com/p/the-case-for-boycotting-generative

Gary Marcus argues that current generative‑AI models fail to meet basic standards of reliability because they routinely hallucinate facts, amplify existing biases, and provide no transparent audit tra

safetygary-marcus--x

Hardware

The OCUDU dApp Platform: An Open Runtime and E3 Interface for Real-Time AI-RAN

arXiv:2609.07843v1 Announce Type: cross Abstract: Machine learning has shown its largest gains in the band below 10 ms inside a 3GPP new radio (NR) 5G distributed unit (DU): link adaptation, per-slot

hardwarearxiv-cs-lg

The Price of Consistency: Exploiting Visual Anchors for Multimodal Jailbreaking in Video Generation

arXiv:2609.07216v1 Announce Type: new Abstract: The rapid evolution of video generation has shifted the paradigm from pure text-driven to multi-conditional controllable generation, with reference imag

Tutorials

The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks

arXiv:2603.25579v2 Announce Type: replace-cross Abstract: A key capability of modern neural networks is their capacity to simultaneously learn underlying rules and memorize specific facts or exception

tutorialsarxiv-cs-lg

Toward Robust Single-Photon Perception for Robots: A Condition-Aware Active Learning Approach

arXiv:2505.04376v2 Announce Type: replace-cross Abstract: LiDAR-based perception plays a fundamental role in modern robotic systems for environment understanding and navigation. Single-photon LiDAR (S

applicationsarxiv-cs-cv

Toward Sustainable Distributed LLM Inference: A Systems Synthesis and Research Agenda for an Energy-, Carbon-, and Cache-Aware llm-d Control Plane

arXiv:2609.05565v1 Announce Type: cross Abstract: Large language model (LLM) sustainability is increasingly a serving-systems problem, not only a training problem. In production, energy and carbon imp

Tracing Mathematical Proficiency Through Problem-Solving Processes

arXiv:2512.00311v3 Announce Type: replace Abstract: Knowledge Tracing (KT) aims to model student's knowledge state and predict future performance to enable personalized learning in Intelligent Tutorin

TransNormal-2: Geometry-Grounded Rectified Flow with Edge-Aware Decoding for Precise Normal Estimation

arXiv:2609.06665v1 Announce Type: new Abstract: Diffusion-based models enable monocular geometry estimation, yet their pixel-space precision is limited by a shared, under-studied error source: VAE rec

Agents

TrojanWorld: Backdooring World-Model Agents via Imagination Steering

arXiv:2609.07051v1 Announce Type: new Abstract: World models increasingly serve as the predictive core of model-based reinforcement learning agents, enabling them to simulate future dynamics and reaso

agentsarxiv-cs-lg

Understanding Uncertainty Sampling via Equivalent Loss

arXiv:2307.02719v5 Announce Type: replace Abstract: Uncertainty sampling is a classical active-learning strategy, yet the statistical objective induced by its query rule is often implicit. We introduc

Unified Long Video Inpainting and Outpainting via Overlapping High-Order Co-Denoising

arXiv:2511.03272v2 Announce Type: replace Abstract: Diffusion-based text-to-video models are increasingly capable, but mask-based editing over hundreds of frames remains challenging: naive long-video

Unified Vision-Centric Pedestrian Crossing Action Prediction via Adaptive Patch Projection and Proactive Spatial Rectification

arXiv:2609.07420v1 Announce Type: new Abstract: Vision cues are available and informative for pedestrian action prediction, but obtaining stable target-centric representations from video frames remain

UniFusion: Sparse-View 4D Reconstruction via Unified Spatio-temporal Depth Alignment

arXiv:2609.05888v1 Announce Type: new Abstract: In this paper, we address the challenging problem of 4D reconstruction from sparse-view videos. This setup usually relies on monocular depth estimation

Tutorials

Unifying Physics-Based Humanoid Interaction with a Context-Conditioned Interaction Prior

arXiv:2609.06591v1 Announce Type: new Abstract: Developing unified physics-based humanoid controllers that can navigate complex 3D scenes and manipulate objects remains a longstanding challenge. Exist

tutorialsarxiv-cs-ro

US-JEPA: A Joint Embedding Predictive Architecture for Ultrasound

arXiv:2602.19322v2 Announce Type: replace Abstract: Ultrasound (US) imaging poses unique challenges for representation learning due to its inherently noisy acquisition process. The low signal-to-noise

VERPO: Verified Evidence Regularized Policy Optimization

arXiv:2609.06100v1 Announce Type: new Abstract: Verifiable outcome rewards guide language-model post-training, but sequence-level advantages do not identify which token-level decisions should be prese

Video Compression with Graph-inspired Neural Representation

arXiv:2609.05541v1 Announce Type: new Abstract: Implicit Neural Representations (INR) provide a compact and content-adaptive paradigm for video compression, typically representing a video through shar

Agents

ViT3Flow: A Test-Time Training Transformer MeanFlow for Postoperative Radiograph Synthesis in Scoliosis

arXiv:2609.05579v1 Announce Type: new Abstract: Predicting postoperative spinal morphology from preoperative radiographs could provide valuable support for scoliosis surgical planning, but remains cha

agentsarxiv-cs-cv

VoT: Vision-of-Thought for Unified Multimodal Representation Alignment

arXiv:2609.07815v1 Announce Type: new Abstract: Current text-to-image systems typically employ a 'text encoder plus diffusion decoder' paradigm, in which text semantics directly modulate continuous la