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Hardware-Aware Features for CUTLASS Kernel Selection

arXiv:2609.35587v1 Announce Type: new Abstract: GPU libraries such as CUTLASS expose tens of thousands of semantically equivalent kernels for a single operation, making exhaustive autotuning expensive

HARMONIA: Interpretable Graph Learning through Mixtures of Neural Bases

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Human DGX agent

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DGX agent

arXiv:2609.33972v1 Announce Type: cross Abstract: Existing interpretable graph additive models still face limitations in either computational scalability or modeling flexibility. In terms of structura

model-releasesarxiv-cs-lg

29 Sept 2026

Harmonizing Spectral Evolution in Conditional Flow Matching for TTS

arXiv:2609.34431v1 Announce Type: new Abstract: Conditional Flow Matching (CFM) models for text-to-speech (TTS) suffer from incoherent frequency evolution during inference. While similar spectral imba

Harness Learning Enables Generalizable Test-Time Adaptation

arXiv:2609.35738v1 Announce Type: cross Abstract: A language-model agent is jointly defined by its model and its harness, the executable program that organizes model calls, tool use, and information f

Harnessing Coupled Stream Completion For Human-Object Ineraction Modeling

arXiv:2609.32551v1 Announce Type: new Abstract: Text-conditioned human-object interaction (HOI) generation requires body motion, object trajectories & rotations, and hand articulation to remain coordi

Helical Tendon-Driven Continuum Robot with Programmable Follow-the-Leader Operation

arXiv:2601.13177v2 Announce Type: replace Abstract: Spinal cord stimulation (SCS) is widely used for pain management and has recently shown promise in promoting functional recovery following spinal co

safetyarxiv-cs-ro

Help Me Help You: The Aggregate Value of Source and Target Data in Transfer Learning

arXiv:2408.16189v3 Announce Type: replace-cross Abstract: Transfer learning, in regression or classification, concerns problems where one aims to use imperfect data from a source distribution P to imp

HERO-MoE: Historical Expert Routing with Scale-Preserving Fusion

arXiv:2609.32581v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures have become a standard way to scale model capacity while keeping computation sparse, yet routing remains a key

HERO: Preserving Structure and Semantics in Heterogeneous Continual Graph Learning

arXiv:2505.17458v3 Announce Type: replace Abstract: Machine learning on heterogeneous graphs has advanced rapidly, driven by the diverse entities, relations, and semantics inherent in real-world data.

applicationsarxiv-cs-lg

HeroFrame-Bench: Reference-Anchored Evaluation via Rubric--Ranking Co-Evolution for Movie Hero Frame Selection

arXiv:2609.32280v1 Announce Type: new Abstract: Hero frames are in-film stills used as source imagery for theatrical posters, streaming cover art, film database listings, and other promotional placeme

safetyarxiv-cs-cv

Local Ai

HGPTrans: Hierarchical Graph-Pooling Transolver for Automotive Aerodynamic Drag Coefficient Prediction

arXiv:2609.31765v1 Announce Type: new Abstract: Accurate and rapid prediction of the aerodynamic drag coefficient (C_D) is essential for vehicle design, particularly during early-stage styling iterati

local-aiarxiv-cs-cv

Hidden Activations are not Enough I: Knowledge Matrices as Higher Representations

arXiv:2609.34166v1 Announce Type: new Abstract: We study the knowledge matrix of a trained feedforward network as a higher representation of its inputs. A network is a pair (W,f), a thin representatio

Hierarchical Clustering and Signal Denoising on Digraphs

arXiv:2609.34670v1 Announce Type: cross Abstract: In this paper, we propose a representation of a digraph (directed graph) as a Hermitian matrix derived from its adjacency matrix. This representation

applicationsarxiv-cs-lg

Hierarchical Frequency-Domain Compression of Implicit Geometric Representations for Large-Scale Point Clouds

arXiv:2609.32789v1 Announce Type: new Abstract: Large-scale point cloud representations of complex geome tries incur prohibitive computational and memory costs, necessitating compressed implicit repre

Hierarchical Multi-agent Reinforcement Learning for Warehouse Robot Coordination under Communication Loss

arXiv:2609.33637v1 Announce Type: cross Abstract: In this paper, we propose a hierarchical multi-agent reinforcement learning framework for coordinating robot teams in warehouse environments under com

safetyarxiv-cs-ro

Tutorials

Hierarchical Response Preservation for Continual Adaptation of Zero-Shot Graph-Text Models

arXiv:2609.33607v1 Announce Type: new Abstract: Pretrained graph-text models align graph representations with textual semantics, enabling recognition of unseen classes and transfer across graph domain

tutorialsarxiv-cs-lg

High-Capacity Robust Medical Image Exfiltration via Neural Network Weight Replacement

model-releasesarxiv-cs-cv

arXiv:2609.31726v1 Announce Type: new Abstract: Collaborative medical AI platforms allow researchers to train models on sensitive imaging data while restricting data export. However, trained models ca

High-Level Text Preprocessing for Semantic Similarity Analysis of Discursive Texts: A Framework and Empirical Demonstration

arXiv:2609.33983v1 Announce Type: cross Abstract: Semantic Textual Similarity (STS) methods assume that a document's lexical content faithfully represents what it asserts. This assumption fails for di

High-Probability Guarantees for SGD under eta-Heavy-Tailed Gradient Noise

arXiv:2609.32195v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is widely used to train machine learning models, but subsampling the training data introduces noise into its updates

HiLoRe: What to Store, Compress, or Recompute for Efficient GRPO Training

arXiv:2609.33570v1 Announce Type: new Abstract: Group-relative policy optimization (GRPO) makes learner-side activations a major memory-computation bottleneck: gradient checkpointing reduces activatio

HM-ROUTER: Joint Model and Harness Routing for Agentic Systems

arXiv:2609.32213v1 Announce Type: new Abstract: Agent performance depends on both the underlying model and the harness that manages its tool use and execution. Selecting a suitable pair requires accou

HOI-Retarget: Contact-Centric Retargeting for Human-Object Interaction

arXiv:2609.34674v1 Announce Type: new Abstract: Learning from demonstration (LfD) has enabled humanoid robots to acquire diverse whole-body skills, but extending this paradigm to human-object interact

researcharxiv-cs-ro

Local Ai

HoTS: Homophily-Aware Temperature Scaling for Graph Neural Network Calibration

arXiv:2609.32426v1 Announce Type: new Abstract: For graph node classification, calibrated class probabilities are needed when confidence scores, usually the maximum predicted class probability, are us

local-aiarxiv-cs-lg

How Does 'English (US)' Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline

arXiv:2604.04204v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly embedded in educational, professional, and public infrastructure, yet widely used platforms expo

How Does Preconditioning Guide Feature Learning in Deep Neural Networks?

arXiv:2509.25637v2 Announce Type: replace Abstract: Preconditioning is widely used in machine learning to accelerate convergence on the empirical risk, yet its role on the expected risk remains undere

Tutorials

How Far Are We from Removing the Visual Encoder? Scaling Laws for Encoder-Free Multimodal Pretraining

arXiv:2609.35457v1 Announce Type: new Abstract: Most modern multimodal large language models (MLLMs) build on a pretrained visual encoder that provides a strong visual prior. Encoder-free MLLMs instea

tutorialsarxiv-cs-cv

How Linear Attention Remembers

arXiv:2609.33093v1 Announce Type: new Abstract: Linear attention replaces the growing key--value (KV) cache of standard attention with a fixed-size recurrent state, substantially reducing memory growt

How Much Imprecision is Enough Imprecision in my Classifier? A Practical Elicitation Procedure

arXiv:2609.33352v1 Announce Type: new Abstract: Set-valued classifiers, whether derived from precise probabilities and an adapted cost function, from convex sets with a robust inference mechanism, or

How Reusable Are Benchmarks with Richer Feedback?

arXiv:2609.32109v1 Announce Type: new Abstract: We study whether benchmarks reliably guide model selection as developers adapt to evaluation feedback across multiple criteria. We find that the worst-c

How Strong Is the Evidence for the Artificial Hivemind? Reevaluating Evidence for the Open-Ended Homogeneity of Language Models

arXiv:2609.33936v1 Announce Type: new Abstract: Recent research argues that language models exhibit pronounced homogeneity in open-ended generation, framing such behavior as an Artificial Hivemind tha

How Synthetic Labels Improve Conformal Prediction: A Perspective on Conditional Coverage

arXiv:2609.33482v1 Announce Type: new Abstract: Conformal prediction provides distribution-free finite-sample marginal coverage, but post-hoc calibration data may be too scarce to learn how uncertaint

Tutorials

How to Loop MoE: Flatten the Experts, Untie the Attention

arXiv:2609.35751v1 Announce Type: new Abstract: Looped Transformers reuse one block of layers several times: by spending extra computation they push a model of fixed size further, and so use its param

tutorialsarxiv-cs-lg

How to Tame a Multi-Headed Hydra? Adaptive Multi-Category Safety Steering for Large Language Models

arXiv:2609.34514v1 Announce Type: cross Abstract: As large language models (LLMs) become increasingly widespread, preventing unsafe responses to harmful prompts is essential for their safe deployment.

HPMD: A Historical Persian Manuscript Dataset for Word Spotting with Line-Level Annotation

arXiv:2609.34490v1 Announce Type: new Abstract: Large collections of historical Persian manuscripts have been digitized, but searching them is still slow and mostly manual. Historians usually want to

safetyarxiv-cs-cv

HRIR-Former: Grid-Free Time-Domain Reconstruction of Head-Related Impulse Responses with a Spatially Encoded Transformer

arXiv:2603.27998v3 Announce Type: replace-cross Abstract: Individualized head-related impulse responses (HRIRs) enable binaural rendering, but dense per-listener measurements are costly. We address HR

Human Activity Recognition via Ultra-Wideband Data: A Framework for Dimensionality Reduction, Pattern Discovery, and Predictive Modeling

arXiv:2609.32008v1 Announce Type: new Abstract: Recent advances in sensor technology have enabled more effective human activity recognition (HAR), particularly in real-time systems with limited comput

applicationsarxiv-cs-lg

Human Motion Prediction for Human-Robot Collaboration

arXiv:2609.32346v1 Announce Type: new Abstract: This paper compares three human motion prediction methods - GMM-based clustering, TransFusion, and Graph-Mixer - evaluating their effectiveness in human

safetyarxiv-cs-ro

HUMAN-TCI: Hierarchical Multi-Stream Motion-Aware Network with Torso-Centered Interaction for Text-to-Motion Retrieval

arXiv:2609.34430v1 Announce Type: new Abstract: Accurate retrieval of human motions is a crucial first step in text-guided human motion modeling and synthesis, as it selects semantically relevant sequ

Humanoid Badminton: Learning Dynamic Racket Skills from Limited Human Motion Data

arXiv:2609.31840v1 Announce Type: new Abstract: High-speed racket sports provide a demanding testbed for humanoid robots, requiring time-critical decisions, precise striking, and dynamic whole-body co

applicationsarxiv-cs-ro

Humanoid Loco-Manipulation With Discrete VLA Model

model-releasesarxiv-cs-ro

arXiv:2609.35709v1 Announce Type: new Abstract: Vision-language-action (VLA) models using discrete action tokens have proven effective for controling robotic arms on manipulation tasks. For a humanoid

Humanoids for Robot-Assisted Surgery: Bimanual Base Placement and Tool-Mount Optimization via Capability Maps

arXiv:2609.33096v1 Announce Type: new Abstract: Rapid advances in humanoid robotics have motivated growing interest in the application of humanoids for healthcare and clinical tasks. However, it remai

applicationsarxiv-cs-ro

Hyperbolic Manifold Constrained Tabular Neural Network

arXiv:2607.09710v2 Announce Type: replace Abstract: Tabular prediction is central to a wide range of real-world applications. Tabular data typically contain heterogeneous features as well as rich and

HyperDAM: Hyperspectral Distractor-Aware Memory with Amodal Expansion for SAM 3 Tracking

arXiv:2609.34396v1 Announce Type: new Abstract: Hyperspectral video provides material cues that can disambiguate targets with similar false-color appearance, yet foundation-model trackers update memor

HyperLabel: Multi-Label Classification via Hypergraph-Based Label Correlation Modeling

arXiv:2609.32276v1 Announce Type: new Abstract: Multi-label classification (MLC) requires predicting multiple relevant labels for each instance, where a central challenge is modeling complex label dep

Agents

ICMAPE: In-Context Multiagent Pure Exploration

arXiv:2609.33986v1 Announce Type: new Abstract: In some multi-agent systems, the quantity to be optimized is not an externally specified reward but the information acquired about unknown properties of

agentsarxiv-cs-lg

Identical Runs, Different Results: Benchmarking AI Coding Agents on Open-Weight Models

arXiv:2609.33812v1 Announce Type: cross Abstract: Repeated runs of the same coding agent are known to give different benchmark scores. We ask what that variation means for a team running an agent on i

Identifiability Limits of Gravitational Wave Phase Deviations: Multiclass Classification with a Multihead Neural Network

arXiv:2609.31993v1 Announce Type: cross Abstract: We study how well gravitational-wave phase deviations can be identified using a neural network with classification and regression heads. The classific

Identifiable Convex-Concave Regression via Sub-gradient Regularised Least Squares

arXiv:2506.18078v2 Announce Type: replace-cross Abstract: We propose a novel nonparametric regression method that models complex input-output relationships as the sum of convex and concave components.