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Growing to See: Efficient Pretraining of Self-Supervised Vision Transformers

arXiv:2610.16817v1 Announce Type: new Abstract: Progressive depth growth builds large networks by starting with shallow models and inserting layers during training. Recent advances in large language m

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GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models

DGX agent

arXiv:2506.10946v3 Announce Type: replace Abstract: Unlearning large language models (LLMs) is important due to copyright and privacy concerns. A key challenge is unintended forgetting, where removing

model-releasesarxiv-cs-lg

14 Oct 2026

Guarded Block Transfers for Polytope Distance: Linear Convergence with Explicit Constants and Gap-Certified Screening for SVM Training

arXiv:2610.15829v1 Announce Type: new Abstract: Hard-margin SVM training is the distance problem between two convex hulls, which the Triangle Algorithm (TA) solves with a certified duality gap. We pro

Tutorials

Guidance Without Labels: Flow Matching from Coupled Gaussian Mixtures

arXiv:2610.16654v1 Announce Type: new Abstract: Flow matching models are typically trained to transport a Gaussian source to the data distribution, with source and target samples paired independently.

tutorialsarxiv-cs-lg

GuidanceNFT: NFT-Based Reward Fine-Tuning of Guided Diffusion Models

arXiv:2610.15856v1 Announce Type: new Abstract: DiffusionNFT (NFT) fine-tunes diffusion models toward task-specific rewards, but optimizing these rewards does not guarantee fidelity to the full prompt

Hardware

H-DDCM: Hadamard Codebooks for Fast Generative Image and Video Compression

arXiv:2610.18125v1 Announce Type: new Abstract: Training-free diffusion-based compression methods repurpose the generative priors of a diffusion or a flow model to compress data without retraining the

hardwarearxiv-cs-cv

Local Ai

HairFlow: Modeling 3D Hair Strands with Multi-Modal Conditioned Diffusion

arXiv:2610.17348v1 Announce Type: new Abstract: Modeling 3D hair strands is challenging due to complex hairstyle geometry, scarce high-quality training data, and incomplete or noisy input observations

local-aiarxiv-cs-cv

HALLMARK: How to Diagnose LLM Citation Verifiers and When to Deploy Them

arXiv:2607.18360v2 Announce Type: replace-cross Abstract: GPTZero found 53 NeurIPS 2025 accepted papers with hallucinated citations, and venues now screen submissions with automated reference checkers

Hallucination-aware Faithful Reasoning in Remote Sensing

arXiv:2610.18369v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated promising capabilities for remote sensing reasoning, yet they frequently generate visually un

safetyarxiv-cs-cv

HaloBlock: Faster and Better Decoding for Diffusion Large Language Models

arXiv:2610.17948v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.

Hand2Robot: Object-Centric 4D Hand Reconstruction from Human Demonstrations for Robotics

arXiv:2610.15769v1 Announce Type: cross Abstract: Human demonstrations can capture task-relevant manipulation without using the target robot, but the recorded hand motions cannot directly serve as rob

safetyarxiv-cs-cv

Hardware-Assisted Multi-Stage Ransomware Detection with Adaptive Machine Learning

arXiv:2610.15951v1 Announce Type: cross Abstract: Ransomware is a fast-escalating privacy threat causing significant financial and data losses worldwide. As attacks grow more sophisticated, traditiona

Hardware-Friendly Token-Group Activation Quantization for Low-Bit Mamba Super-Resolution

arXiv:2610.16261v1 Announce Type: cross Abstract: Mamba-based super-resolution models are efficient alternatives to Transformer-based restoration backbones, but their low-bit post-training quantizatio

Harmonic Representations in Symbolic Music Transformers are Localized and Controllable

arXiv:2610.15957v1 Announce Type: cross Abstract: Transformer models trained on symbolic music have become remarkably capable. However, it is yet unclear how they represent music structure, and whethe

Harness^2: Recursive Agent Harnessing for an Open World

arXiv:2610.14224v1 Announce Type: cross Abstract: LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a p

Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation

arXiv:2610.15431v1 Announce Type: new Abstract: Monocular depth estimation (MDE) has emerged as a cost-effective alternative to hardware-dependent 3D sensing modalities, yet predicting precise metric

applicationsarxiv-cs-cv

Harnessing VLM in Embodied RL: From Reward Regressor to Success Detector via Exploration-Augmented Key-Observation Gating

arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat

applicationsarxiv-cs-lg

HarnessTTT: Learn to Optimize Harness at Test-Time for Scientific Discovery

arXiv:2610.17370v1 Announce Type: new Abstract: Scientific discovery with language models requires finding the best valid solution within a finite computational budget. We study how feedback from this

HASTE: Hierarchical and Attribute-aware Supervision for Generative Recommendation

arXiv:2610.17368v1 Announce Type: cross Abstract: Generative recommendation models have shown promising results by representing items as semantic IDs and generating these IDs autoregressively. We intr

Agents

Have You Seen It Clearly? Uncertainty-Guided Belief Refinement for Zero-Shot Object Navigation

arXiv:2610.15375v1 Announce Type: new Abstract: Zero-Shot Object Navigation (ZSON) requires an agent to locate target objects in unfamiliar environments without additional training for the test catego

agentsarxiv-cs-ro

Heading Hierarchy Reconstruction for Complex and Long Documents with Level-Wise Multimodal Memory

model-releasesarxiv-cs-cv

arXiv:2610.18238v1 Announce Type: new Abstract: Vision-language models (VLMs) have been widely adopted for document parsing and optical character recognition (OCR), as they can accurately extract page

HelpMeOut: A Neuropsychology-Grounded Benchmark for Error-Aware Monitoring of Household Task Execution

model-releasesarxiv-cs-ro

arXiv:2610.17694v1 Announce Type: new Abstract: We introduce HelpMeOut, an embodied AI benchmark for error-aware monitoring of household task execution. Existing embodied household benchmarks typicall

Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models

arXiv:2610.15781v1 Announce Type: new Abstract: Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically cons

Heuristics are Not Enough: Calibrated and Corrected Caching for Video Diffusion Acceleration

arXiv:2610.16545v1 Announce Type: new Abstract: Feature caching has become a mainstream training-free strategy for accelerating video diffusion models by reusing intermediate outputs across denoising

safetyarxiv-cs-cv

HGA-Quant: Heterogeneity-Aware Quantization for AutoRegressive Visual Generation Models

arXiv:2610.15297v1 Announce Type: new Abstract: Recently, AutoRegressive Visual Generation (ARVG) models have emerged as a competitive paradigm for high-quality image synthesis. However, their substan

applicationsarxiv-cs-cv

Hierarchical Curriculum Learning for Surgical Video Generation: Focusing on Bilateral Axillo-Breast Approach Robotic Thyroidectomy Datasets

model-releasesarxiv-cs-cv

arXiv:2610.17684v1 Announce Type: new Abstract: High-fidelity surgical video generation is increasingly important for surgical education, simulation, and downstream AI training, as conventional simula

Agents

Hierarchical Multi-Agent Reasoning Systems for Knowledge-Grounded Material Substitution

arXiv:2610.14123v1 Announce Type: cross Abstract: AI-assisted scientific discovery increasingly seeks to move beyond generating plausible ideas toward reproducible, constraint-aware workflows that can

agentsarxiv-cs-lg

Hierarchical Planning with Latent World Models

arXiv:2604.03208v3 Announce Type: replace Abstract: World models are a promising path to zero-shot embodied control through planning. However, existing world model planners struggle on long-horizon, m

applicationsarxiv-cs-lg

Hierarchical Time Series Forecasting with Operator-Valued Kernels

arXiv:2610.18196v1 Announce Type: cross Abstract: Hierarchical time series forecasting requires generating accurate predictions that are coherent across multiple levels of aggregation. Existing method

applicationsarxiv-cs-lg

HierarchiRetina: A Diabetic Retinopathy Screening and Grading Cascade with Heterogeneous Mixture-of-Experts Lesion Segmentation

arXiv:2610.17933v1 Announce Type: new Abstract: Clinical screening for diabetic retinopathy proceeds in stages, yet most automated systems grade fundus images with a single black-box network. Three ga

High-fidelity Three-Dimensional Flow Field Reconstruction Driven by Turbulent Fluid Dynamics

arXiv:2610.18045v1 Announce Type: cross Abstract: High-fidelity three-dimensional turbulent flow fields are essential for scientific and engineering analyses, yet obtaining them through direct numeric

High-Order Error Bounds for Markovian LSA with Richardson-Romberg Extrapolation

arXiv:2508.05570v2 Announce Type: replace-cross Abstract: In this paper, we study the bias and high-order error bounds of the Linear Stochastic Approximation (LSA) algorithm with Polyak-Ruppert (PR) a

Hiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids

arXiv:2601.07718v2 Announce Type: replace Abstract: Achieving robust humanoid locomotion in complex, unstructured environments requires transitioning from reactive proprioception to proactive percepti

safetyarxiv-cs-ro

HiPAD: A Unified Gait, Audio-Visual, and Personality Fusion Network for Depression Detection, with a Hierarchical Personality Ablation and the Calibration Limits of Domain-Adapted LLMs

arXiv:2610.14961v1 Announce Type: cross Abstract: We present HiPAD, a single fusion network submitted to all six sub-tracks of the MPDD-AVG 2026 depression-detection challenge, covering the Elder and

Tutorials

HiSTOR: Structured Treatment-outcome Representation Learning for High-Dimensional Longitudinal Data

arXiv:2610.17739v1 Announce Type: new Abstract: Estimating potential outcomes under alternative treatment sequences is essential for personalized decision-making, but remains challenging with high-dim

tutorialsarxiv-cs-lg

Historical Anchors for Scientific Forecasting on Human-Aware Knowledge Graphs

arXiv:2610.14023v1 Announce Type: new Abstract: Predicting which scientific connections will form next can point researchers toward the most promising leads. One successful approach learns representat

History, Adaptation, and Hidden Gain: Two Prospective Tests of Learned Predictive Control in a Synthetic Neural Population

arXiv:2610.14368v1 Announce Type: new Abstract: We study learned one-step predictive control of a synthetic population of 64 leaky integrate-and-fire neurons whose light sensitivity is scaled by a hid

History Replays Itself: Unleashing Long-Context Capability in Linear Attention

arXiv:2610.15715v1 Announce Type: cross Abstract: Linear attention promises the efficiency needed for long-context language modelling, yet its fixed-size recurrent state must simultaneously support on

HodgePhaseNet: Discrete Hodge Decomposition of Semantic Flows in Transformer Attention

arXiv:2610.14971v1 Announce Type: new Abstract: WavePhaseNet introduced frequency-resolved semantic representations, QuantumPhaseNet introduced gauge-covariant phase connections, and ModularPhaseNet m

Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization

arXiv:2603.21862v2 Announce Type: replace Abstract: Scaling laws govern macroscopic resource allocation for LLMs, yet precise architectural configurations for Mixture-of-Experts (MoE) models remain gu

Local Ai

Honeycomb Crystal in a Mass-Asymmetric Electron-Hole Bilayer

arXiv:2610.17030v1 Announce Type: cross Abstract: A two-dimensional electron gas in a uniform neutralizing background forms a triangular Wigner crystal at low density. In a strongly mass-asymmetric el

local-aiarxiv-cs-lg

How Low Can You Go: Fine-Tuning LLMs with Bayesian Optimization (LlMBO)

arXiv:2610.18504v1 Announce Type: cross Abstract: Recently, Morris et al. introduced TinyLoRA, a strategy for LLM fine-tuning which introduces arbitrarily few parameters, and demonstrated accuracy imp

How Shared Representations Become Specialized: Formation, Maintenance, and Latent Susceptibility

arXiv:2610.15830v1 Announce Type: new Abstract: When several predictions use the same internal representation, information about some targets can remain easier to recover than information about others

How the Classical Baseline Shapes Machine-Learning Speed Claims in Topology Optimization

arXiv:2610.16051v1 Announce Type: cross Abstract: Topology optimization places material so that a structure resists deformation under given loads. Machine-learning methods often report large speed-ups

How to Build a Benchmark That Actually Measures Taste

model-releasesarxiv-cs-cv

arXiv:2610.14707v1 Announce Type: cross Abstract: Expert-aligned 'taste' benchmarks should reward craft judgment, not the ability to game the test. We introduce TasteBench, a pairwise good-vs-bad benc

How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints

arXiv:2511.18606v2 Announce Type: replace-cross Abstract: Latent safety filters extend Hamilton-Jacobi (HJ) reachability to operate on latent state representations and dynamics learned directly from h

How Vision Transformers Represent Position: A Mechanistic Comparison of Absolute and Rotary Positional Encodings

arXiv:2610.13992v1 Announce Type: new Abstract: Positional embeddings encode the spatial position of each image patch in a Vision Transformer (ViT), allowing the model to distinguish different spatial

Human-Inspired Asymmetric Collaboration for Dual-Student Semi-Supervised Medical Image Segmentation

arXiv:2610.18133v1 Announce Type: new Abstract: Dual-student learning enriches predictive diversity in SSMIS by introducing a strongly augmented view alongside a weakly augmented view. Insufficient st