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arXiv:2609.13035v1 Announce Type: new Abstract: Symmetries play a central role in reducing the complexity of reinforcement learning problems, yet most existing approaches rely on fixed group actions o

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

DGX agent

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

researcharxiv-cs-lg

14 Sept 2026

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

model-releasesarxiv-cs-cl

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

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

model-releasesarxiv-cs-cv

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

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

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

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

Look Before You Leap: Pre-Action Verification for LLM Agents

arXiv:2609.11957v1 Announce Type: new Abstract: An LLM agent acts on the world by emitting actions: shell commands to run, edits to apply. A wrong action does not always fail loudly; it can fail silen

MAxBench: A Multinomial Concept Recovery Benchmark

model-releasesarxiv-cs-cl

arXiv:2609.13072v1 Announce Type: cross Abstract: Fine-grained control of language model behaviors (e.g., steering) is among the more actionable outcomes of interpretability research. For binary conce

On Universality of Non-Separable Approximate Message Passing Algorithms

arXiv:2506.23010v2 Announce Type: replace-cross Abstract: Mean-field characterizations of first-order iterative algorithms -- including Approximate Message Passing (AMP), stochastic and proximal gradi

PEARL: Structural Privacy-Utility Control in Human-Centric CPS via Personalized Early-Exit Deep Reinforcement Learning

arXiv:2403.05864v3 Announce Type: replace Abstract: In human-centric Cyber-Physical Systems (CPS), personalized Deep Reinforcement Learning (DRL) agents must share fine-grained control actions with cl

Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence

arXiv:2609.12036v1 Announce Type: new Abstract: In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from v

safetyarxiv-cs-ro

PhD branding question [R]

researchr-machinelearning

I'm starting a PhD where I will be doing Graph ML (somewhere along the lines of graph signal processing/ graph deep learning.) My eventual goal is research scientist at big tech, or whichever company

PhysioAI: Clinical Knowledge-Guided Semantic Supervision for Skeleton-Based Physiotherapy Action Recognition

arXiv:2609.12491v1 Announce Type: new Abstract: Skeleton-based action recognition can support automated tracking of physiotherapy exercises, particularly in remote rehabilitation settings where contin

researcharxiv-cs-cv

Prism-SQA: An Interpretable and Adaptable Neural Framework for Surface Electromyography Quality Assessment

arXiv:2609.12724v1 Announce Type: cross Abstract: sEMG is vulnerable to various contaminants that distort signal morphology and spectral content. Accurate signal quality assessment (SQA) is essential

QTrans: A Quantum Transformer for Sentiment Classification

arXiv:2609.12011v1 Announce Type: new Abstract: In small-scale binary sentiment classification scenarios, factors such as negation, contrastive shifts, and cross-word dependencies lead to the non-line

Local Ai

R9V Update: now ~100 tok/s in TG on Qwen3.8 Flash Next IQ4_XS on x2 R9700 + 128GB RAM. Fixed crashes with n-gram SSD streaming, improved diagnostics, plus pinned images. Q4_K_XL now supported, 50 tok/s TG.

Pushed out this new update, hopefully decreases the instances of crashes. I torture tested this one for ~12 hours after my fixes and found no instability. Q4 K XL needs more fine tuning, which I will

local-air-localllama

Tutorials

Repair Before Reinforce: Context-Augmented Knowledge Graph Reasoning for Multi-Hop Question Answering

arXiv:2609.12230v1 Announce Type: new Abstract: Question-answering often requires reasoning across multiple connected facts rather than retrieving a single isolated relation. Knowledge graphs (KGs) pr

tutorialsarxiv-cs-cl

Robust Underwater Grasping of Sloped Objects with a Waterproof Passive Adaptive Gripper

arXiv:2609.12927v1 Announce Type: new Abstract: Robust grasping of everyday objects remains challenging for parallel-jaw grippers, particularly when handling sloped or asymmetric items that induce tor

safetyarxiv-cs-ro

Scalable Discrete-to-Continuous Channel Simulation for Compression and Privacy

arXiv:2609.12067v1 Announce Type: new Abstract: Channel simulation has recently emerged as a useful component in machine learning systems where samples from a prescribed probability distribution are t

Scenario-Independent Criticality Assessment and Prediction for Vulnerable Road Users in Autonomous Driving

arXiv:2609.11947v1 Announce Type: cross Abstract: Increasing safety is the primary objective of automated vehicles. Achieving this goal requires reliable safety metrics that incorporate safety-relevan

safetyarxiv-cs-cv

TokenMapper: A Step Toward Interoperable Speech Token Translation

arXiv:2609.12563v1 Announce Type: new Abstract: Neural audio codecs discretize speech into token sequences, but the resulting token spaces differ in vocabulary and codebook structure, preventing direc

Towards Sustainable Hydrogen Systems: Supply Chain Optimization with Model Predictive Control and Reinforcement Learning

arXiv:2609.11933v1 Announce Type: cross Abstract: Hydrogen supply chains are expected to play a central role in future low-carbon energy systems by enabling renewable energy integration, long-duration

Tutorials

Transfer Learning for Evolving Domains

arXiv:2609.13039v1 Announce Type: new Abstract: Transfer learning explores how to leverage knowledge from various tasks or domains (sources) to enhance predictive performance in related tasks or domai

tutorialsarxiv-cs-lg

Tunable Latent Generative Priors for Compressed Sensing and Inverse Problems

arXiv:2603.07357v3 Announce Type: replace Abstract: Latent generative models have emerged as powerful priors for solving inverse problems. These models typically represent a class of natural signals a

Agents

Want to build a domain-specific agent harness? This is a great practical guide by @sydneyrunkle on designing and building your own custom ag…

Want to build a domain-specific agent harness? This is a great practical guide by @sydneyrunkle on designing and building your own custom agent harness. Worth reading if you’re exploring agentic syste

agentsharrison-chase--x

13 Sept 2026

A Time-Based Readout for Vector-Matrix Multiplication in Fully Analog Memristive SNNs

arXiv:2609.11713v1 Announce Type: cross Abstract: Artificial neural networks rely on vector-matrix multiplications (VMMs), whose implementation in von Neumann architectures is dominated by costly data

researcharxiv-cs-ai

Amulet: a Python Library for Assessing Interactions Among ML Defenses and Risks

arXiv:2509.12386v3 Announce Type: replace-cross Abstract: Machine learning (ML) models are susceptible to various risks to security, privacy, and fairness. Most defenses are designed to protect agains

safetyarxiv-cs-ai

Automating Quadratic Unconstrained Binary Optimization (QUBO) Formulation Generation from Natural Language

model-releasesarxiv-cs-ai

arXiv:2609.10629v1 Announce Type: new Abstract: Quadratic Unconstrained Binary Optimization (QUBO) is a central formulation for combinatorial optimization and has gained increasing attention due to it

Tutorials

DCO: Dynamic Cache Orchestration for LLM Accelerators through Predictive Management

arXiv:2512.07312v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) is pushing AI accelerators toward increasingly powerful and specialized designs. Instead of

tutorialsarxiv-cs-ai

Agents

Generating a Consistent Enterprise: Synthesis and Reference-Free Evaluation of Multi-System Business Data

arXiv:2609.11286v1 Announce Type: new Abstract: Synthetic relational data is normally produced by a model trained on a real dataset, and its quality is measured as the distance to that dataset. This p

agentsarxiv-cs-ai

NovGauge: A Fine-Grained Benchmark for Diagnosing LLMs' Capability in Paper Novelty Assessment

model-releasesarxiv-cs-ai

arXiv:2609.11234v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchma

Local Ai

Physics-Informed Neural Networks to Infer the Perpendicular Energy Conductivity in the Scrape-Off Layer of Stellarator Devices

arXiv:2609.11628v1 Announce Type: cross Abstract: In this work, we develop an inverse Physics-Informed Neural Network (PINN) framework to infer the dependence of the scrape-off layer (SOL) perpendicul

local-aiarxiv-cs-ai

3 Highlights from Thomas Kurian’s Keynote at the Goldman Sachs Communicopia & Technology Conference

model-releasesgoogle-cloud-ai

On Tuesday, September 8, Thomas Kurian participated in the Goldman Sachs Tech Conference, providing an update on Google Cloud’s business and strategy. Here are the highlights:Full Stack Approach: Goog

A Short Survey of Viewing Large Language Models in Legal Aspect

arXiv:2303.09136v2 Announce Type: replace Abstract: Large language models (LLMs) have transformed many fields, including natural language processing, computer vision, and reinforcement learning. These

safetyarxiv-cs-cl

Are We Really Doing Few-Shot Learning? A Critical Examination of Pre-Training Assumptions

arXiv:2609.10851v1 Announce Type: new Abstract: Few-shot learning is commonly evaluated under protocols that pre-train a model on a large auxiliary set whose classes are disjoint from the target episo

safetyarxiv-cs-cv

AUC Maximization from Biased Positive-unlabeled Data with Confidence

arXiv:2609.10928v1 Announce Type: new Abstract: Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced binary classification. Although positiv

safetyarxiv-cs-lg

Automated multi-class wound assessment using dedicated instance segmentation models for boundary detection and classification

arXiv:2603.27325v2 Announce Type: replace Abstract: Accurate wound classification (WC) and boundary segmentation are essential for guiding clinical decisions in chronic and acute wound management. How

researcharxiv-cs-cv

Local Ai

CEM-TUDASR: Computationally efficient multi-modality transformer based unsupervised domain adaptive super-resolution approach

arXiv:2609.11201v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) enables non-invasive visualization of the gastrointestinal tract, but its miniaturized optics, sensor limitations, and

local-aiarxiv-cs-cv

Certifying Lower Bounds for Risk-Sensitive Reinforcement Learning under Adversarial State Perturbations

arXiv:2609.10866v1 Announce Type: new Abstract: Reinforcement learning (RL) agents deployed in real-world environments are often vulnerable to adversarial perturbations in state observations, creating

Coherent Floquet quantum reservoirs for molecular property prediction

arXiv:2609.11071v1 Announce Type: cross Abstract: Quantum reservoir computing (QRC) uses quantum dynamics to represent input histories for prediction through a trained classical readout. Discrete time

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture

model-releasesarxiv-cs-cv

arXiv:2607.09835v2 Announce Type: replace Abstract: The recently introduced YOLO26 architecture incorporates NMS-free end-to-end inference and is optimized for deployment on resource-constrained CPU-b

DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

arXiv:2609.10796v1 Announce Type: new Abstract: Pretrained diabetic retinopathy (DR) prediction models differ in their input fields, serialization formats, preprocessing requirements, and output seman

E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets

model-releasesarxiv-cs-cl

arXiv:2609.11334v1 Announce Type: new Abstract: Natural Language Inference processes pairs of sentences to extract their semantic relations. NLI has been a hot research topic, integrated as a main com

Learning structural balance of graphs from quantum spectral features

arXiv:2609.11736v1 Announce Type: cross Abstract: We develop a quantum approach to spectral feature extraction from the density of states (DOS) of a problem-dependent Hamiltonian, and apply it to mach

LoopVAE: Recurrent Depth Across Scales for Visual Tokenization

model-releasesarxiv-cs-cv

arXiv:2609.11516v1 Announce Type: new Abstract: Hierarchical visual tokenizers typically allocate different processing blocks to different spatial scales. We ask how much of this computation can use t

'Mirror' Large Language Model Evaluations of Depression are Criterion Contaminated

arXiv:2508.05830v3 Announce Type: replace Abstract: Large Language Model (LLM) studies that use language responses elicited from depression assessments to predict scores on those same assessments ofte

researcharxiv-cs-cl