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Hierarchical Continuous Diffusion Language Models

arXiv:2610.02193v1 Announce Type: cross Abstract: Discrete diffusion language models offer a compelling alternative to autoregressive generation for tasks demanding bidirectional reasoning and global

HierGF: Hierarchical Gaussian Fields via Geometry-perception Message Passing for Sparse-view 3D Reconstruction

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Human DGX agent

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DGX agent

arXiv:2610.01056v1 Announce Type: new Abstract: Sparse view 3D reconstruction is an important and common scenario in multimedia applications, such as augmented reality/virtual reality (AR/VR) content

safetyarxiv-cs-cv

2 Oct 2026

High-Value Synthetic Supervision for Parameter-Efficient Adaptation of a Compact Japanese Speech Model

arXiv:2610.00026v1 Announce Type: cross Abstract: Private domain speech is difficult to collect and redistribute, while compact models need task-specific supervision. We study an auditable synthetic p

High Volatility and Action Bias Distinguish LLMs from Humans in Group Coordination

arXiv:2604.02578v2 Announce Type: replace-cross Abstract: Humans exhibit remarkable abilities to coordinate in groups. As large language models (LLMs) become more capable, it remains an open question

Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry

arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly

Applications

Higher-Order Positional Encodings for Graph Representation Learning

arXiv:2610.01903v1 Announce Type: new Abstract: Many real-world systems exhibit higher-order interactions among groups of entities that cannot be captured by pairwise relationships alone. Graph Transf

applicationsarxiv-cs-lg

HiPhy: Hierarchical Alignment for Physically-Plausible Multi-Principle Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.02197v1 Announce Type: new Abstract: Video generation models have achieved remarkable visual fidelity and have strong potential to become general-purpose world simulators. Despite this prog

Hob-VL: A Benchmark for Visually Grounded Boolean Reasoning

arXiv:2610.01605v1 Announce Type: cross Abstract: Reliable visual reasoning requires composing multiple visual observations and returning consistent answers to logically equivalent questions. We intro

Homomorphic Advantage Operator: Stabilizing Reinforcement Learning Under Fully Homomorphic Encryption Constraints

arXiv:2610.02074v1 Announce Type: new Abstract: Privacy-preserving machine learning presents significant deployment challenges on the cloud for intelligent systems with confidential data. Fully Homomo

Agents

How AI Agents Discover Scientific Equations: From Hydrotope Rediscovery to New Water-Wave Amplitudes

arXiv:2610.00435v1 Announce Type: cross Abstract: We study how AI agents discover and validate scientific formulas using a controlled case study of the hydrotope, a recently discovered geometric formu

agentsarxiv-cs-ai

How Divergence Becomes Decision Flips in Compressed Language Models

arXiv:2610.00694v1 Announce Type: cross Abstract: Compression reports summarize how far a compressed language model moved from the dense one, usually by a KL divergence; a deployment that relies on th

How Far is Adam from Natural Gradient Descent?

arXiv:2610.00004v1 Announce Type: new Abstract: Adam is the standard optimizer in deep learning, yet its geometric relationship to natural gradient descent (NGD) contains unresolved questions. We stud

How Many Categories Are Enough? Distribution-Free Certification Limits for Few-Shot Anomaly Thresholds

arXiv:2610.00236v1 Announce Type: new Abstract: Few-shot anomaly detectors are judged by ranking metrics, yet deployment requires an alarm threshold with a controlled false-alarm rate (FAR). We ask ho

Tutorials

How many labelers do you have? A closer look at gold-standard labels

arXiv:2206.12041v3 Announce Type: replace-cross Abstract: The construction of most supervised learning datasets revolves around collecting multiple labels for each instance, then aggregating the label

tutorialsarxiv-cs-lg

How Much Can Language Models Gain from Test-Time Computation?

arXiv:2610.01110v1 Announce Type: new Abstract: How much can test-time computation improve a language model, and at what cost? Test-time scaling is widely proposed as a substitute for larger models, b

HumanoidToolBench: Benchmarking Humanoid Tool Use from Selection to Mobile Execution

arXiv:2610.02089v1 Announce Type: cross Abstract: As robotic hardware and learning methods advance, humanoids need tools to perform tasks beyond their inherent physical limits. Successful tool use req

HumanoidTTT: Test-Time Capability Reuse for Efficient Humanoid Control

arXiv:2610.00198v1 Announce Type: new Abstract: Recent advances in motion generation and whole-body tracking have enabled humanoid robots to execute increasingly diverse motions, yet the same motion c

researcharxiv-cs-ro

HydroJEV: A one-second, training-free screen for cyber-attack and fault attribution in water distribution networks

arXiv:2610.02048v1 Announce Type: new Abstract: When a SCADA alarm is raised in a water distribution network, operators must decide quickly whether it reflects a cyberattack, a physical fault, a norma

iADD: Improving Alignment and Diversity in Diffusion Policy Optimization

arXiv:2610.01789v1 Announce Type: cross Abstract: Reinforcement learning based post training of diffusion models, such as Denoising Diffusion Policy Optimization (DDPO), optimizes a reverse diffusion

Hardware

ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization

arXiv:2610.01445v1 Announce Type: new Abstract: UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochasticity can lead to unstable embeddings across reru

hardwarearxiv-cs-lg

Improving Math Reasoning through Value-guided Informative Search

arXiv:2610.01080v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has substantially improved the mathematical reasoning capabilities of large language models. Recen

Improving scoring functions for protein-protein docking with LambdaLoss

arXiv:2610.00191v1 Announce Type: cross Abstract: Modeling protein-protein interactions requires accurate scoring functions that can rank potential poses (conformations) of a protein-protein complex t

In CEM, a World Model Is Also a Proposal Mechanism

arXiv:2610.00921v1 Announce Type: new Abstract: The cross-entropy method (CEM) uses world-model scores to select action sequences and fit the distribution sampled in its next iteration. A scoring erro

In-context Learning of Single-index Targets: Comparing Kernel and Feature Learners

arXiv:2610.01712v1 Announce Type: new Abstract: In-context learning (ICL) enables a pretrained model to infer a task from demonstrations without updating its parameters. While much of the existing the

In Dialogue with Intelligence: Toward Insightful Co-Augmentation

arXiv:2505.22767v4 Announce Type: replace-cross Abstract: Dialogue with a large language model can lead a person to insight: a sudden change in how they understand a problem. This perspective asks how

In Vino Veritas and Vulnerabilities: Examining LLM Safety via Drunk Language Inducement

arXiv:2601.22169v2 Announce Type: replace-cross Abstract: Humans are susceptible to undesirable behaviours and privacy leaks under the influence of alcohol. This paper investigates drunk language, i.e

Incident-Arena: Getting agents to the last nine of reliability

arXiv:2610.00648v1 Announce Type: new Abstract: AI coding agents are ubiquitous in engineering workflows amongst industry and academia. Yet, despite their use in app coding, relatively less attention

Increasing Width Allows Greedy Layer-wise Training to Rival End-to-End Backpropagation in Self-Supervised Learning

arXiv:2610.00753v1 Announce Type: cross Abstract: End-to-end backpropagation has been the dominant mode of training in deep learning, allowing for the coordination of parameter updates across layers o

INDEQS: Informed Neural controlled Differential EQuationS

arXiv:2606.19138v2 Announce Type: replace Abstract: Neural Controlled Differential Equations (NCDE) provide a powerful continuous-time framework for forecasting time series, but standard graph-based e

Local Ai

IndoorBEV: A Lightweight Real-Time LiDAR BEV Perception System for Indoor Mobile Robots

arXiv:2610.00355v1 Announce Type: new Abstract: Efficient indoor LiDAR perception is challenging because mobile robots must understand cluttered three-dimensional environments under strict latency and

local-aiarxiv-cs-ro

Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation

arXiv:2610.00793v1 Announce Type: cross Abstract: We consider the estimation of drift, diffusion, and noise covariance from discrete observations of stochastic differential equations driven by Gaussia

Inferring Multi-Timescale Neural Dynamics with Switching Linear Dynamical Systems

arXiv:2610.01786v1 Announce Type: new Abstract: Neural activity often exhibits multiple timescales that can vary with behavioral states and task conditions. Identifying these timescales from neural re

Tutorials

Information propagation dynamics in Deep Graph Networks

arXiv:2410.10464v3 Announce Type: replace Abstract: Graphs are a highly expressive abstraction for modeling entities and their relations, such as molecular structures, social networks, and traffic net

tutorialsarxiv-cs-lg

Initial condition recovery in nonlinear damped viscous photoacoustic tomography using a convolutional neural network-guided gradient-free optimization framework

arXiv:2610.01015v1 Announce Type: cross Abstract: Photoacoustic tomography (PAT) is a hybrid imaging modality that combines high optical contrast with high ultrasonic resolution for biomedical imaging

Initialization Improves LLM-Driven Discovery

arXiv:2610.00707v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been used for novel discovery of algorithms, theorems, drugs, and other tasks through the use of harnesses that prom

Integrating Fairness and Explainability in a Multiple Instance Reinforcement Learning System

arXiv:2610.00035v1 Announce Type: new Abstract: Predicting student performance from educational interaction data requires models that are both accurate and sufficiently transparent to support meaningf

safetyarxiv-cs-lg

Local Ai

Interaction-Stiffness-Guided Basis Allocation in Dynamic Movement Primitives for Efficient Skill Transfer

arXiv:2610.01288v1 Announce Type: new Abstract: Dynamic Movement Primitives (DMPs) provide a compact and stable formulation for trajectory representation and generalization in robot skill learning. Ho

local-aiarxiv-cs-ro

Agents

InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation

arXiv:2610.02196v1 Announce Type: cross Abstract: We study test-time evolution for humanoid loco-manipulation: solving tasks that a controller was never trained for by repurposing its existing skills,

agentsarxiv-cs-cv

Interpretable Synthetic Medical Tabular Data Generation for Clinical Decision Support Using Fuzzy Cognitive Maps

arXiv:2610.00391v1 Announce Type: cross Abstract: Synthetic medical tabular data generation has become essential for developing and validating computer-based medical systems (CBMSs) when real clinical

Interpreting Reasoning of Large Language Models via Partial Information Decomposition

arXiv:2610.00571v1 Announce Type: cross Abstract: Large reasoning models (LRMs) have achieved substantial improvements in solving complex mathematical problems, but often produce lengthy, repetitive,

InterviewSim: A Scalable Framework for Interview-Grounded Personality Simulation

arXiv:2602.20294v2 Announce Type: replace-cross Abstract: Simulating real personalities with large language models requires grounding generation in authentic personal data. Existing evaluation approac

Invent a Dataset: Measuring dataset generation abilities with zero seed

arXiv:2610.01674v1 Announce Type: new Abstract: Building datasets remains one of the most manual and brittle parts of AI development. In this technical report, we focus on the most extreme but also mo

Tutorials

IQS-BO: In-Context Query Selection for Bayesian Optimisation

arXiv:2610.01269v1 Announce Type: new Abstract: Bayesian Optimisation (BO) is a powerful framework for the optimisation of expensive black-box functions, but typically requires refitting a surrogate a

tutorialsarxiv-cs-lg

IrekoGPT: Turning Structured Pruning into Post-Hoc Slimmable LLMs

arXiv:2610.00426v1 Announce Type: new Abstract: We introduce IrekoGPT, a post-hoc method for converting pretrained LLMs into slimmable models whose width can be adjusted at inference time. Building on

Is it Possible to Generate Irreversible PolyProtected Templates from Face Embeddings using System-Specific Keys?

arXiv:2610.01385v1 Announce Type: cross Abstract: This work aims to answer the question of whether it is possible to generate irreversible protected templates when the PolyProtect biometric template p

researcharxiv-cs-cv

Is Success All You Need? Investigating the Impact of Input Perturbations on VLA Behaviour in Tabletop Manipulation Tasks

model-releasesarxiv-cs-ro

arXiv:2610.01351v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have achieved high task success rates on robot manipulation task benchmarks. More recently, there has been an emphas

Local Ai

iSEE: Object Permanence Through Self-Supervision

arXiv:2610.01201v1 Announce Type: new Abstract: Object permanence, keeping track of an object's identity and position while it is occluded, is central to video representations that track, predict and

local-aiarxiv-cs-cv

Agents

It Takes Workflows to Evolve Better Workflows

arXiv:2610.01026v1 Announce Type: cross Abstract: Tackling complex real-world tasks can exceed the capabilities of a single large language model (LLM), motivating the use of multi-agent workflows that

agentsarxiv-cs-ai