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hardwarer-machinelearning

I'm a first year ML PhD at a T5 ML program in the US. I managed to get a first author paper accepted to NeurIPS Main Track last month and thought I'd start applying for PhD research internships since

13 Oct 2026

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Flama: 8 years building a Python framework where ML models and LLMs are first-class, now written up on arXiv [P]

DGX agent

I started Flama in 2018 to take a trained model to a production API with as little ceremony as possible. With 2.0 LLMs became first-class alongside classic models, and together with Miguel Durán-Olive

local-air-machinelearning

13 Oct 2026

Hardware

A hyper realism Krea2 model generate Magazine page with multiple photos in one shot -

hardwarer-stablediffusion

I’ve wanted this for a long time: a Krea-2 model that gives you a magazine page in one shot. Flash-lit gravure sets, film grain, multi-photo layouts on white paper, big headlines, covers and back cove

Benchmarking Embedding Geometries and Clustering Algorithms for Unsupervised Patent Claim Classification

arXiv:2610.12997v1 Announce Type: new Abstract: Prior-art retrieval systems are structurally organized around classification codes, making cross-code discovery difficult. This paper asks if an unsuper

CNN-Transformer with Sigmoid Label for High-Resolution Sub-Degree DOA Estimation

arXiv:2610.13433v1 Announce Type: cross Abstract: This paper addresses the grid quantization error of deep-learning (DL)-based direction-of-arrival (DOA) estimation. Classification- based DOA methods

Cooperative Aerial Transportation of a Payload with a Sliding Cable Attachment

arXiv:2610.13665v1 Announce Type: new Abstract: This paper presents a dual-quadrotor hook- suspended transport system for cooperative aerial manipulation of a payload that is not rigidly attached to a

researcharxiv-cs-ro

Data-Adaptive Mahalanobis Metric Learning for Cross-Head Attention in Transformers

arXiv:2610.13261v1 Announce Type: new Abstract: In this paper, we propose Data-Adaptive Mahalanobis Cross-Head Attention (DAMCHA), a simple and effective attention mechanism that generalizes Multi-Hea

Data-Driven Stochastic Optimal Control in Reproducing Kernel Hilbert Spaces

arXiv:2407.16407v3 Announce Type: replace-cross Abstract: This paper proposes a fully data-driven approach for optimal control of nonlinear control-affine systems represented by a stochastic diffusion

agentsarxiv-cs-lg

JEPA-kMMVAE: CSI Prediction for Time-Varying Wireless Channels

arXiv:2610.13315v1 Announce Type: cross Abstract: This paper considers channel state information (CSI) prediction using neural networks for time-varying multi-antenna channels from noisy historical ob

Learning Size Independent Constraint Models from Input Data and Positive and Negative Example Solutions

arXiv:2610.13640v1 Announce Type: new Abstract: In this paper we describe a Constraint Acquisition Tool that generates size independent constraint programs from input data and positive and negative ex

Localized Generative Design of Ship Hulls with Diffusion Models and High-Fidelity Assessment

model-releasesarxiv-cs-ai

arXiv:2610.12870v1 Announce Type: cross Abstract: Practical ship design requires localized refinement and performance evaluation. This paper presents a reward-directed diffusion framework for localize

Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics

arXiv:2610.12518v1 Announce Type: cross Abstract: This position paper argues that the generative molecular dynamics (GenMD) community is not properly evaluating its progress: current evaluations let a

Looped Diffusion Transformer: the same blocks run several times inside each denoising step, and loop depth can be changed at sampling time [R]

researchr-machinelearning

Paper: Looped Diffusion Transformer (arXiv 2609.40305, 30 Sep). Instead of making a text-to-image DiT bigger, it runs a shared group of transformer blocks several times inside each denoising step. The

MathVis: Can AI Reason through Drawing? A Benchmark for Mathematical Figure Generation

model-releasesarxiv-cs-ai

arXiv:2610.12954v1 Announce Type: new Abstract: This paper introduces MathVis, a benchmark designed to evaluate LLMs' ability to visualize frontier mathematical problems and perform diagram-assisted r

Mixture of Many Zero-Compute Experts: A High-Rate Quantization Theory Perspective

arXiv:2510.03151v2 Announce Type: replace Abstract: This paper uses classical high-rate quantization theory to provide new insights into mixture-of-experts (MoE) models for regression tasks. Our MoE i

Multimodal Image-based Robotic Assistance and Guidance Environment (MIRAGE): A Novel Unified Framework for Surgical Navigation and Visualization

arXiv:2610.12780v1 Announce Type: new Abstract: This paper presents the computational architecture and quantitative preclinical evaluation of MIRAGE, a multimodal image-guided robotic surgery framewor

researcharxiv-cs-ro

Tutorials

One-Step Text Generation by Seq-Drifting

arXiv:2610.12879v1 Announce Type: new Abstract: Diffusion language models generate tokens in parallel, but still require multiple sampling steps to produce high-quality text. In this paper, we investi

tutorialsarxiv-cs-ai

Representation Alignment from a Few Paired Data via Distilled Optimal Transport

arXiv:2610.12781v1 Announce Type: new Abstract: Aligning two independently pretrained unimodal encoders typically demands millions of paired examples. In this paper, we study the regime where only N s

safetyarxiv-cs-ai

Toward Maximizing Algebraic Connectivity via Density-Dependent Backbone Construction and Reinforcement Learning Completion

arXiv:2610.12697v1 Announce Type: cross Abstract: This paper studies an open network design problem of constructing graph topologies with maximum algebraic connectivity under fixed numbers of vertices

U4RASD at KnowledgeGraphEval-2026: Ontology-Constrained Encoder and LLM Systems for Arabic Relation Extraction

model-releasesarxiv-cs-cl

arXiv:2610.12742v1 Announce Type: new Abstract: This paper details our submission to KnowledgeGraphEval 2026 Subtask 2 on directed Arabic relation extraction. We explored encoder-based and large langu

Introducing Multi-Agent Self-Supervision (MASS): Recursive self-improvement through collective intelligence Blog: https://pub.sakana.ai/mass…

Introducing Multi-Agent Self-Supervision (MASS): Recursive self-improvement through collective intelligence Blog: https://pub.sakana.ai/mass/ As AI systems tackle increasingly open-ended research prob

safetydavid-ha--x

11 Oct 2026

Hardware

Nvidia reportedly in early talks to buy, acquihire or invest more in Reflection AI

Nvidia Corp. is in early talks to acquire open-weight model developer Reflection AI Inc. or invest more in the startup, according to the Financial Times. People familiar with the matter told the paper

hardwaresiliconangle

11 Oct 2026

A Survey on Industrial Anomaly Synthesis

arXiv:2502.16412v3 Announce Type: replace Abstract: This paper presents a comprehensive review of industrial anomaly synthesis (IAS). Existing surveys on industrial anomalies mainly focus on anomaly d

Applications

AI-Mediated Self: How HCI Defines and Relates to the Self

arXiv:2610.10770v1 Announce Type: cross Abstract: How might AI alter how we understand and experience the self? This scoping review analyzes 102 papers to examine how the self is defined in the field

applicationsarxiv-cs-ai

Beyond the Ergodic Wall: A Discrete Geometric Physics Sandbox for Analysing AI Scaling Limits and Complexity Collapse

arXiv:2610.10651v1 Announce Type: cross Abstract: This paper exposes the ergodic ceiling and thermodynamic inefficiency of current deep learning, which converges to a statistical average of historic h

safetyarxiv-cs-ai

Demonstrating Arena 5.0: A Photorealistic ROS2 Simulation Framework for Developing and Benchmarking Social Navigation

model-releasesarxiv-cs-ro

arXiv:2610.11220v1 Announce Type: new Abstract: Building upon the foundations laid by our previous work, this paper introduces Arena 5.0, the fifth iteration of our framework for robotics social navig

Applications

DLC: A Metric-Guided Dynamic Loss Controller for Multi-Objective Training

arXiv:2610.11433v1 Announce Type: new Abstract: In this paper, we introduce a metric-guided dynamic loss controller (DLC) for multi-objective image restoration. Conventional image restoration pipeline

applicationsarxiv-cs-cv

From Log-Odds to Shapley Values: An Explanatory Geometry for the Weighted Naive Bayes Classifier

arXiv:2610.10642v1 Announce Type: cross Abstract: This paper studies the construction of an explanatory space for a weighted naive Bayes classifier from the supervised representation induced by the mo

Tutorials

Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform

arXiv:2509.24001v3 Announce Type: replace Abstract: This paper evaluates the current gaze estimation methods within a human-robot interaction (HRI) context of a shared workspace scenario. We introduce

tutorialsarxiv-cs-cv

Graphons of Line Graphs

arXiv:2409.01656v4 Announce Type: replace-cross Abstract: We consider the problem of estimating graph limits, known as graphons, from observations of sequences of sparse finite graphs. In this paper w

LinSlot: Exploiting Linear Representation hypothesis for unsupervised attribute discovery from slot based object representation

arXiv:2610.10722v1 Announce Type: cross Abstract: This paper studies the problem of learning disentangled representations of objects and their attributes from raw, unstructured image data. Slot-based

ProtoSemImage: Image-Valued Prototypes with Deformable Row Alignment for Interpretable Document Classification

model-releasesarxiv-cs-ai

arXiv:2610.11460v1 Announce Type: cross Abstract: Prototypes in classification models are almost always vectors, and a vector has no readable form. This paper asks what happens when a prototype is an

Stride Independent Patching for Deep Learning

arXiv:2610.12216v1 Announce Type: new Abstract: This paper presents semi-automatic stride-independent patching (SSP) as an alternative to automatic stride-dependent patching techniques. SSP uses user

The Kinetics Observer: A Tightly Coupled Estimator for Legged Robots

arXiv:2406.13267v2 Announce Type: replace Abstract: This paper presents the Kinetics Observer, a novel proprioceptive state estimator for legged robots designed to provide the feedback required for ve

researcharxiv-cs-ro

Transmission Neural Networks: Inhibitory and Excitatory Connections

arXiv:2604.04246v2 Announce Type: replace-cross Abstract: This paper extends the Transmission Neural Network model proposed by Gao and Caines in [1]-[3] to incorporate inhibitory connections and neuro

Walking on Roofs: Exploring the Potential of Walking Robots for Construction Work on Roofs

arXiv:2610.12272v1 Announce Type: new Abstract: This paper investigates the feasibility of deploying quadruped walking robots for the automation of work in roof environments. While quadrupeds have dem

safetyarxiv-cs-ro

Wieszcz-XIX: A 3.1-Billion-Word Corpus of Pre-1918 Polish and Temporally Bounded Language Models Trained From Scratch

arXiv:2610.10592v1 Announce Type: new Abstract: Historical Polish is well documented as a language but annotated in machine-readable form only to about a million words for the period this paper covers

researcharxiv-cs-cl

Allocation Stability and Wald Inference under Variance-Aware UCB

arXiv:2412.08843v3 Announce Type: replace-cross Abstract: Allocation stability is often used to justify Gaussian inference from bandit data, but when is it necessary? In this paper, we address this qu

safetyarxiv-cs-lg

Anytime-Feasible First-Order Optimization via Safe Sequential QCQP

arXiv:2511.19675v2 Announce Type: replace-cross Abstract: This paper presents the Safe Sequential Quadratically Constrained Quadratic Programming (SS-QCQP) algorithm, a first-order method for smooth i

agentsarxiv-cs-ro

Batch Augmentation with Unimodal Fine-tuning for Multimodal Fusion of Large Language Models

arXiv:2505.06592v2 Announce Type: replace Abstract: In this paper, we propose batch augmentation with unimodal fine-tuning for multimodal learning. We start with pre-trained unimodal models. We fine-t

Context-aware Attention-based Gaussian Mixture Models for Vehicular Trajectory Prediction

arXiv:2610.09174v1 Announce Type: new Abstract: Reliable and interpretable trajectory prediction is critical for cooperative and autonomous driving in complex and uncertain environments. This paper in

agentsarxiv-cs-lg

Design of a Fully Actuated 4-DOF Robotic Finger With Joint-Specific Hybrid Remote Actuation

arXiv:2610.10180v1 Announce Type: new Abstract: This paper presents a fully actuated 4-DOF robotic finger using a joint-specific hybrid remote-actuation architecture. The metacarpophalangeal (MCP) joi

agentsarxiv-cs-ro

From Expert-Guided Proof Search to Automated Open-Problem Solving

arXiv:2610.09769v1 Announce Type: cross Abstract: Large language models are increasingly contributing to mathematical research, where progress often depends on efficient proof search, incremental impr

agentsarxiv-cs-cl

Gaussian Density Splatting Network

arXiv:2610.10396v1 Announce Type: new Abstract: This paper proposes a novel crowd counting approach, the Gaussian Density Splatting Network (GDSNet). Unlike methods that rely on conventional, grid-bas

Insights from Autoresearch for Solar Panel Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.10491v1 Announce Type: new Abstract: This paper investigates AutoResearch, a protocol in which a coding language model edits a training program under a one-hour GPU budget and retains a cha

Lightweight and Versatile Learned Optimization by Recombination of Gradient History

arXiv:2610.09604v1 Announce Type: new Abstract: This paper presents a lightweight and versatile learned optimizer that dynamically recombines gradient history, represented as averages over disjoint ti

Order-Optimal Sample Complexity of Rectified Flows

arXiv:2601.20250v2 Announce Type: replace Abstract: Recently, flow-based generative models have shown superior efficiency compared to diffusion models. In this paper, we study rectified flow models, w

Persistence Paradox in Dynamic Science: Evidence from the Deep Learning Revolution

arXiv:2506.22729v3 Announce Type: replace-cross Abstract: Persistence is often regarded as a virtue in science. In this paper, however, we challenge this conventional view by highlighting its contextu

safetyarxiv-cs-lg