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Hidden in Rounds: Predicting the Time Cost of 802.11 Contention in Federated Learning

arXiv:2609.12903v1 Announce Type: new Abstract: Federated learning over IEEE~802.11 shares the wireless channel among clients that send model updates. We use ns-3 to measure the frame-delivery ratio a

safetyarxiv-cs-lg

Local Ai

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Hierarchical Prototype Emergence in Modern Hopfield Models

DGX agent

arXiv:2609.12079v1 Announce Type: cross Abstract: Hierarchical correlations are a universal feature of any realistic model of data, and the question of how associative memory models may learn these co

local-aiarxiv-cs-lg

14 Sept 2026

Agents

High-Fidelity Multi-Body Simulator for Autonomous Racing

arXiv:2609.12795v1 Announce Type: new Abstract: We present a custom high-fidelity vehicle dynamics simulation environment for testing and validation of Autonomous Racing software. The digital twin of

agentsarxiv-cs-ro

High-Probability Convergence of SGD via Batched Updates

arXiv:2609.12765v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is the primary workhorse for large-scale optimization. While the average behavior of its iterates, typically charact

Hardware

HoliBench: A Cross-Platform Benchmarking and Deployment Toolkit for Foundation Models in CPS-IoT Applications

arXiv:2609.12412v1 Announce Type: cross Abstract: Foundation models, including large language models, vision-language models, and time-series foundation models, are increasingly deployed on embedded a

hardwarearxiv-cs-lg

HSI-Road Relabeled: Surface-Aware Road-Scene Segmentation

arXiv:2609.12151v1 Announce Type: new Abstract: The HSI-Road dataset provides paired RGB and 25-channel NIR (600--960~nm) images with binary masks but no surface-level labels.~This paper introduces a

researcharxiv-cs-cv

Hurdle-RMIL: Addressing Zero Inflation and Long-Tailed Imbalance in Infrared Rainfall Retrieval

arXiv:2510.20486v2 Announce Type: replace Abstract: Imbalanced labels can cause frequent samples to dominate AI-based quantitative remote sensing, degrading rare-event retrieval. In rain-rate retrieva

Hyperion: An AI-powered HPC cluster for sciences and humanities research that utilizes ML for predicting job turnaround time

arXiv:2609.11946v1 Announce Type: cross Abstract: Hyperion is an innovative high-performance computing (HPC) cluster developed for researchers in both science and humanities disciplines at the Univers

HypoKG: Evidence-Disciplined Biomedical Hypothesis Generation Beyond Endpoint Knowledge

arXiv:2609.12260v1 Announce Type: new Abstract: Large language models (LLMs) can generate biomedical hypotheses, but it remains unclear whether they truly reason from scientific evidence or simply pro

I Am No One: Style-Aware Paraphrasing for Text Anonymization

arXiv:2609.12341v1 Announce Type: new Abstract: Authorship attribution models can re-identify users from seemingly anonymized text by exploiting stable stylistic fingerprints, even after explicit iden

Impact of Multiple Non-Invasive Biosignals on Cardiovascular Biomarker Estimation via Simulation-Based Inference

arXiv:2609.11969v1 Announce Type: cross Abstract: As the population ages, the number of patients with cardiovascular diseases continues to increase, highlighting the need for early detection before pr

IMPLY: Physically Anchored Consistency for World-Model Rollouts

arXiv:2609.12441v1 Announce Type: cross Abstract: A world model asked what happens if an object is pushed at several speeds produces several futures. If the model has the object in mind, those futures

researcharxiv-cs-cv

Improving Imitation Learning Efficiency for Manipulation through Geometric Prior Pretraining

arXiv:2609.12721v1 Announce Type: new Abstract: Applying an imitation learning policy to a new manipulation task usually requires collecting new demonstrations and retraining the model, which makes sa

safetyarxiv-cs-ro

In-Hospital Stroke Risk-State Classification from PPG-Derived Hemodynamic Features

arXiv:2602.09328v2 Announce Type: replace Abstract: The scarcity of temporally aligned pre-event physiological data limits the study of stroke risk states before documented clinical recognition. We fo

Agents

Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics

arXiv:2605.06377v2 Announce Type: replace-cross Abstract: We study Nash equilibrium learning in partially observable Markov games (POMGs), a multi-agent reinforcement learning framework in which agent

agentsarxiv-cs-lg

Inference for Newton Methods with Accelerated Sketch-and-Project via Random Scaling

arXiv:2609.12421v1 Announce Type: cross Abstract: We study an online sketched Newton method that approximates the Newton direction at each step via a state-of-the-art sketching solver, called the gene

Inferring Dislocation Microstructures from X-ray Diffraction via Cross-Modal Contrastive Learning

arXiv:2609.12713v1 Announce Type: cross Abstract: Understanding and inferring dislocation microstructures from diffraction patterns remains an open challenge in materials characterization, as diffract

safetyarxiv-cs-lg

Information-Induced Training Geometry: Exact Reduction, Canonical Completion, and Structured Expressivity

arXiv:2609.12991v1 Announce Type: new Abstract: Training data constrains optimizer geometry through the covectors visible to a declared information channel. We study how such partial information deter

Information Specialization and Constrained Synthesis in Multi-Agent LLM Forecasting: A Prospective Live-Study of the 2026 FIFA World Cup

arXiv:2609.12495v1 Announce Type: cross Abstract: Large language models are being organized into multi-agent systems with specialized roles, but whether such specialization produces distinct forecasts

Input Resolution Matters: Real-Time Object Detection Latency

arXiv:2609.12920v1 Announce Type: new Abstract: We model total latency as the convolution of preprocessing, inference, and postprocessing distributions under a simplifying independence approximation,

Applications

InRTL: Effective Intra-Inter Interaction Learning for Relational Tables

arXiv:2609.12712v1 Announce Type: new Abstract: Relational table learning has recently emerged as an important research direction for modeling multiple tables connected through primary key-foreign key

applicationsarxiv-cs-lg

Inverting Self-Triggered Control: Adversarial Reinforcement Learning for Sparse Denial-of-Service Attacks

arXiv:2609.12016v1 Announce Type: new Abstract: Self-triggered reinforcement learning control (RL-STC) learns the sparsest control schedule that preserves Lyapunov-decreasing stability under a Run-Tim

safetyarxiv-cs-lg

Investigating Temporal Motion Features for Pose-to-Text Indian Sign Language Translation

arXiv:2609.12993v1 Announce Type: cross Abstract: We investigate the effect of pretrained T5 model scale and explicit motion features on pose-to-text Indian Sign Language Translation (SLT) for the WSL

Is Bash All You Need? An Empirical Study of Tool Interfaces for Enterprise Digital Worker Agents

arXiv:2609.11999v1 Announce Type: cross Abstract: In this study, we examine whether a general shell can outperform specialized tools on enterprise tasks. Shell-based agents have shown strong results i

Is Multilingual LLM Watermarking Truly Multilingual? Scaling Robustness to 100+ Languages via Back-Translation

arXiv:2510.18019v3 Announce Type: replace Abstract: Multilingual watermarking aims to make large language model (LLM) outputs traceable across languages, yet current methods still fall short. Despite

Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Surface-Level Feature Leakage

arXiv:2609.13003v1 Announce Type: new Abstract: Binary-choice truth benchmarks ask models to choose between a correct and an incorrect answer, but if the two answers differ systematically in surface-l

KAD-Net: Kinematics-Aware Decoupled Learning for Robust 3D Hand Pose Estimation from a Single Depth Image

arXiv:2609.12559v1 Announce Type: new Abstract: Due to the complexity of hand kinematics and self-occlusion, existing 3D hand pose estimation methods based on single depth images struggle to comprehen

KoSimpleQA: A Korean Factuality Benchmark with an Analysis of Reasoning LLMs

arXiv:2510.18368v2 Announce Type: replace Abstract: We present extbf{Korean SimpleQA (KoSimpleQA)}, a benchmark for evaluating factuality in large language models (LLMs) with a focus on Korean cultura

Kraken: LLM-based Speech-to-Speech Translation via Low-bitrate VQ and Dual-path Source Conditioning

arXiv:2609.13045v1 Announce Type: new Abstract: Speech-to-speech translation (S2ST) has advanced significantly with speech LLMs, offering the potential for joint optimization and preserving non-lingui

Label-Guided Knowledge Distillation for 3D-CNNs in Action Recognition

arXiv:2609.13024v1 Announce Type: new Abstract: As a key model compression technique, knowledge distillation aims to transfer knowledge from a high-capacity teacher model to a lightweight student mode

Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models

arXiv:2609.12105v1 Announce Type: cross Abstract: The prevailing assumption in applied machine learning is that progress on consequential quantitative decisions such as pricing risk, allocating capita

Large Distant Gradients Need Not Be Reliable: reliability-weighted credit assignment for long-horizon autoregressive forecasting

model-releasesarxiv-cs-lg

arXiv:2609.12890v1 Announce Type: new Abstract: In autoregressive forecasting, long prediction rollouts provide distant supervision, but backpropagation through time (BPTT) carries gradients from thos

LatentVerse: A Framework for Understanding Shared and Modality-Specific Information in Multimodal Latent Representations

arXiv:2609.12364v1 Announce Type: new Abstract: Latent embeddings have become a central data abstraction in modern machine learning, especially in biomedicine, where foundation models are increasingly

Layered Safety: Enhancing Autonomous Collision Avoidance via Multistage CBF Safety Filters

arXiv:2603.00338v2 Announce Type: replace Abstract: This paper presents a general end-to-end framework for constructing robust and reliable layered safety filters that can be leveraged to perform dyna

safetyarxiv-cs-ro

Applications

Learning-Augmented Optimization for Strategic Two-Echelon Spare Parts Network Design

arXiv:2609.12524v1 Announce Type: cross Abstract: We study the strategic design of a two-echelon spare-parts inventory network where evaluating each candidate topology requires an expensive inventory

applicationsarxiv-cs-lg

Learning Interaction Kernels from Collective Steady States

arXiv:2609.12004v1 Announce Type: cross Abstract: We propose a learning procedure for system identification in interacting particle systems from single-snapshot observations of collective behaviors, u

Learning Sign Language Recognition under Label Noise: A Study of Noise-Robust Losses for Isolated and Continuous Settings

arXiv:2609.12885v1 Announce Type: new Abstract: In sign language recognition, the isolated (ISLR) classification loss treats a single label as ground truth, as does the frame-level auxiliary classifie

safetyarxiv-cs-cv

Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging

arXiv:2606.14957v4 Announce Type: replace Abstract: Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic an

researcharxiv-cs-cv

Learning the Geometry of Collider Events with Metric-Aware Deep Sets

arXiv:2609.12024v1 Announce Type: cross Abstract: Optimal transport gives structured data a geometry, but exact evaluation is costly in large pairwise analyses that exploit relationships among distanc

LettuceVisSim: A Simulator That Generates Lettuce Image Time-series for Vision-Based Reinforcement Learning

arXiv:2609.12505v1 Announce Type: new Abstract: Vision-based reinforcement learning holds strong potential for decision-making in controlled environment agriculture (CEA). However, its development is

safetyarxiv-cs-cv

Local Ai

LG-PF: Lightweight Confidence-Guided Polarization Image Fusion

arXiv:2609.12787v1 Announce Type: new Abstract: Polarization image fusion combines the stable luminance and structural information of the total- intensity image S0 with the material-sensitive details

local-aiarxiv-cs-cv

LGFN: Lightweight Gated RGB-Polarization Fusion with Modality-Availability Conditioning for Camouflaged Object Detection

arXiv:2609.12798v1 Announce Type: new Abstract: Camouflaged object detection (COD) is an important engineering task in intelligent optical perception, but it remains challenging when targets closely r

Agents

LifeMem: Enabling Lifelong Experience Reuse for LLM Agents

arXiv:2609.12655v1 Announce Type: new Abstract: Large language model agents are expected to continuously adapt to new tasks and environments over their lifetime by reusing past experience. However, ex

agentsarxiv-cs-cl

Limits of LLM Text Detectors in Education

arXiv:2508.08096v2 Announce Type: replace Abstract: Students increasingly use the assistance of large language models (LLMs) in their academic writing. While slight assistance (e.g., grammar and style

Linear Exponential Quadratic Gaussian Covariance Steering

model-releasesarxiv-cs-lg

arXiv:2609.12463v1 Announce Type: cross Abstract: We formulate and analyze the linear exponential quadratic Gaussian (LEQG) covariance steering problem in continuous time over a given deadline (finite

LLM-BabyBench: Can Language Models Plan in Worlds They Can Simulate?

arXiv:2505.12135v2 Announce Type: replace-cross Abstract: When an interactive benchmark reports a single success rate for a language-model agent, it is rarely clear what that number measures. A failur

LLM Compression by Block Removal with Constrained Binary Optimization

arXiv:2602.00161v3 Announce Type: replace-cross Abstract: In this paper, we formulate the compression of large language models (LLMs) by optimally deleting transformer blocks (``block removal'') as a

LLM-Enhanced Dual-Branch Learning for Large-Scale Multi-Label Text Classification

arXiv:2609.12915v1 Announce Type: new Abstract: Large-scale multi-label text classification assigns a small subset of relevant labels to each document from a vocabulary containing thousands or tens of