All entries

Modular Norm RandOpt: Population-Efficient Ensembling through Architecture-Aware Perturbations

arXiv:2609.25745v1 Announce Type: new Abstract: RandOpt samples weight-perturbed language models and ensembles top-ranked candidates through plurality voting, but its global perturbation scale ignores

Content type

All Blog X Post Paper YouTube Reddit GitHub

Model Releases

MOLA LiDAR-Inertial Odometry (MOLA-LIO) on the COMFORT Localization Benchmark

DGX agent

arXiv:2609.25813v1 Announce Type: new Abstract: This short report documents our entry to the COMFORT Localization Benchmark (IROS 2026), evaluated on the GrandTour dataset recorded with the Boxi paylo

model-releasesarxiv-cs-ro

23 Sept 2026

Agents

MoM: Memory of Memory

arXiv:2609.25054v1 Announce Type: new Abstract: For a long-horizon LLM agent, the memory question is not what was once recorded but what currently holds. Most designs answer it only indirectly: every

agentsarxiv-cs-cl

MorphoSHAP: Rethinking the Unit of Attribution in Explanation for Deep Visual Models

arXiv:2609.25815v1 Announce Type: new Abstract: Visual attribution methods typically explain predictions using pixels, superpixels, or regular patches. These representations can localize important reg

local-aiarxiv-cs-cv

Most mental health benchmarks focus on emergency situations. MentalHealthBench is designed to cover the full spectrum of mental health conve…

Most mental health benchmarks focus on emergency situations. MentalHealthBench is designed to cover the full spectrum of mental health conversations that people bring to AI - from everyday support to

model-releasesopenai--x

MotionForge: A Data Generation Pipeline and Large-Scale Benchmark for Long-Horizon Manipulation of Dynamic Objects with Domain Shifts

model-releasesarxiv-cs-ro

arXiv:2609.25689v1 Announce Type: new Abstract: Recent advances in learning-based robot policies have demonstrated promising progress, yet they are predom- inantly evaluated in static or quasi-static

Moving6DPoSe: A Multimodal Database for Monocular 6D Pose Estimation and Segmentation of Moving Objects

arXiv:2609.26161v1 Announce Type: new Abstract: Estimating the 6D pose of moving objects remains challenging due to motion blur and the limited temporal resolution of conventional frame-based cameras.

applicationsarxiv-cs-cv

Tutorials

MSA-CITE: A Co-Adapted LoRA Specialist Ecology for Fixed-Budget Small-Model Inference

arXiv:2609.26217v1 Announce Type: new Abstract: Compact language models are typically deployed by retaining a single post-training checkpoint and sampling it repeatedly. In this work, we challenge thi

tutorialsarxiv-cs-lg

MT-ProtBERT: Multi-task Learning ProtBERT for Intrinsically Disordered Proteins Classification with Scarce Data

arXiv:2609.25334v1 Announce Type: new Abstract: Intrinsically disordered proteins (IDPs) differ from folded proteins in that they are dynamic, lack a stable three-dimensional conformation, and have lo

Multi-Axis Selective Decoupling Framework for Free-Floating Space Manipulators

arXiv:2609.26267v1 Announce Type: new Abstract: Free-floating space manipulator systems face operational challenges due to dynamic coupling. While traditional reactionless manipulation eliminates base

researcharxiv-cs-ro

Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

arXiv:2609.25179v1 Announce Type: new Abstract: Predicting the remaining useful life (RUL) is essential for effective predictive maintenance. Spatio-Temporal Graph Neural Networks (ST-GNNs), which can

Multi-View Fair Clustering Guided by Cross-View Sensitive Information Discrepancy

arXiv:2609.25811v1 Announce Type: new Abstract: Multi-view clustering (MVC) aims to uncover latent cluster structures by exploiting complementary information from multiple views. Despite substantial p

MultiViewDx: Evidence-Linked Multi-View Clinical Diagnosis

arXiv:2410.14948v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) can perform well on existing medical visual question answering (MedVQA) benchmarks, but their train

applicationsarxiv-cs-cl

Must-read paper from Google on self-improving agent harnesses. If you auto-optimize your agent's harness, your eval score can go up while th…

Must-read paper from Google on self-improving agent harnesses. If you auto-optimize your agent's harness, your eval score can go up while the agent gets worse on real tasks. This paper shows how to pr

model-releasesdair-ai--x

NaCR: Visual Localization via NeRF-aided Camera Ray Regression

arXiv:2609.25907v1 Announce Type: new Abstract: Visual localization (VL) is a fundamental technology for vision applications such as virtual reality. Recently, a novel VL paradigm, Camera Ray Regressi

local-aiarxiv-cs-cv

Nathan Lambert's written Congressional testimony on the state of open models - Chinese open-weight downloads now 2x America's, >80% of OpenRouter open-model usage

model-releasesr-localllama

Worth a read if you track open weights. Nathan Lambert (interconnects) posted the written version of his Congressional testimony on where open models stand. The numbers that got me: Hugging Face downl

NavSafe-infty: Benchmarking Closed-Loop Driving Safety in Photorealistic Environments

model-releasesarxiv-cs-ro

arXiv:2609.26618v1 Announce Type: new Abstract: End-to-end (E2E) driving policies have progressed rapidly on open-loop (OL) benchmarks, yet OL evaluation cannot reveal whether a policy withstands comp

NAWE: Digital Watermarking with Neural-Assisted Watermark Extraction

arXiv:2609.25972v1 Announce Type: new Abstract: NAWE (Neural-Assisted Watermark Extraction) combines an explicit signal-processing watermarking construction with a pretrained neural host predictor. A

Neighbor-Aware Token Reduction via Hilbert Curve for Vision Transformers

arXiv:2512.22760v2 Announce Type: replace Abstract: Vision Transformers (ViTs) have achieved remarkable success in visual recognition tasks, but redundant token representations limit their computation

NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping

arXiv:2510.14827v3 Announce Type: replace Abstract: Safe and efficient robot operation in complex human environments can benefit from good models of site-specific motion patterns. Maps of Dynamics (Mo

applicationsarxiv-cs-ro

Neoadjuvant chemotherapy response prediction using pretreatment diffusion and contrast-enhanced magnetic resonance imaging with clinical variables

arXiv:2609.26105v1 Announce Type: cross Abstract: Prediction of pathological complete response before neoadjuvant chemotherapy may facilitate more tailored therapeutic planning for breast cancer patie

Neural Approximation by Function Composition: Rigidity and Doubly Exponential Convergence

arXiv:2609.25874v1 Announce Type: new Abstract: Deep neural networks approximate functions by composing affine maps with nonlinear activations, but how composition itself creates approximation power i

New paper! 🫡 We introduce Matryoshka Attribution, a new attribution method which uses gradient descent to find which parts of a neural netw…

model-releasesyohei-nakajima--x

New paper! 🫡 We introduce Matryoshka Attribution, a new attribution method which uses gradient descent to find which parts of a neural network are responsible for a behaviour. MAttr is #1 on the Mecha

New user - seeking help

I’m looking for advice as I’ve just started out the local llm journey. I’d like to try out coding. I downloaded LM Studio and Qwen3.8-27B-Q4, but I wonder if there are more optimal options for my hard

local-air-localllama

NextLM brings its precision prospecting agent to Google Cloud Marketplace

model-releasessiliconangle

NextLM Inc., which makes software that uses behavioral analysis and custom artificial intelligence models to help sales professionals identify and rank individual sales leads, is bringing its AI Prosp

Norm2Tex: Augmenting Visuo-Tactile Simulations with Texture

arXiv:2609.25398v1 Announce Type: new Abstract: Large-scale datasets are essential for training generalist robot control policies. Collecting real-world tactile data is costly and time-consuming, moti

applicationsarxiv-cs-ro

Agents

NostrAgent: A Decentralized Identity and Delegation Architecture for Sovereign Agentic Systems

arXiv:2609.22944v1 Announce Type: cross Abstract: Autonomous AI agents increasingly act across organizational boundaries on behalf of human operators: they invoke third-party services, delegate subtas

agentsarxiv-cs-ai

Not All 4-bit Quantizers Are Equal: Deployment-Time Mitigation of PII Leakage in Fine-Tuned Small Language Models

arXiv:2609.25014v1 Announce Type: cross Abstract: Organizations fine-tune small language models on private data and then compress them to 4 bits for resource-efficient deployment. We show that the com

local-aiarxiv-cs-lg

Tutorials

Note that this is an experimental model meant to show how you can train your own specialized decision models fairly easily! You can also che…

Note that this is an experimental model meant to show how you can train your own specialized decision models fairly easily! You can also check out the model weights here, along with the full tutorial

tutorialstogether-ai--x

Notes on Fourier-Bessel wavelets

arXiv:2609.26537v1 Announce Type: new Abstract: These notes develop the mathematical foundations and construction of a Fourier-Bessel wavelet family inspired by the disk harmonics of Shaqfa et al.[9].

NPLSD: Accelerating Line-Segment Detection on NPU Microcontrollers

model-releasesarxiv-cs-cv

arXiv:2609.25022v1 Announce Type: cross Abstract: Line-segment detection is fundamental to robotics, autonomous navigation, and industrial inspection. While transformer-based detectors achieve the hig

NPU Accelerator: Quantized Real-Time Vehicle Detection on PYNQ-Z1 Using FINN

arXiv:2609.24757v1 Announce Type: cross Abstract: This paper presents the design, optimization, implementation, and on-board validation of a neural processing unit (NPU) accelerator for real-time vehi

researcharxiv-cs-ai

Observed Control - Linearly Scalable Nonlinear Model Predictive Control with Adaptive Horizons

arXiv:2508.13339v2 Announce Type: replace-cross Abstract: This work highlights the duality between state estimation and model predictive control. A model predictive controller, observed control, is pr

researcharxiv-cs-ro

Observer Choice and Threshold Selection in Retinal Vessel Segmentation: A Subject-Separated Evaluation

arXiv:2609.25597v1 Announce Type: new Abstract: The annotation used to select a segmentation threshold is part of the evaluation protocol, yet its effect is easily conflated with model quality. We exa

Offloaded inference for real-world physical AI robotics

applicationsmicrosoft-research

Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and

Ollama serve doesn't work on linux

Is it just me or ollama serve command doesn't work at all. It uses a different directory than the systemd process, so it can't find any model or anything if you installed it using systemd ollama. Luck

local-air-ollama

OMatG-flash: An All-Atom Flow Map with Reinforce Adjoint Matching for Scalable Materials Discovery

arXiv:2609.26402v1 Announce Type: new Abstract: The discovery of novel inorganic materials drives technological breakthroughs in critical fields such as computing and energy storage. Generative AI has

OmniEcho: Spatial Audio Understanding for Embodied Agents

model-releasesarxiv-cs-ai

arXiv:2609.23407v1 Announce Type: cross Abstract: Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for emb

On Basis Function Selection for Sparse Gaussian Process Regression

arXiv:2609.26624v1 Announce Type: cross Abstract: Sparse Gaussian processes achieve O(N) inference by replacing the kernel with an appropriate expansion in a fixed basis {phi_j} on the input space. Gi

On Probabilistic Inference Through Parametric Tensor Decomposition in Base Tensor Networks

arXiv:2609.23774v1 Announce Type: new Abstract: Probabilistic inference is generally only tractable in low-treewidth graphical models, limiting its effective applicability in high-treewidth settings.

researcharxiv-cs-ai

On stage with @MistralAI . 🔥 From building models to putting them into the hands of developers, a closer look at how Mistral is shaping the…

model-releasesarthur-mensch--x

On stage with @MistralAI . 🔥 From building models to putting them into the hands of developers, a closer look at how Mistral is shaping the next generation of AI products. Straight from the #AIEParis

On the Effect of Bit-Level Parameter Perturbations in Machine Learning and Deep Learning Models

arXiv:2609.26280v1 Announce Type: new Abstract: In this chapter, we investigate how classical machine learning models respond to small, targeted modifications in their parameters. We compare and contr

On the Gradient Heterogeneity Dynamics of Adversarially Robust Federated Regression

arXiv:2609.25705v1 Announce Type: cross Abstract: Federated learning (FL) is intrinsically heterogeneous: honest clients may have different data-generating models. On top of that, adversarial clients

On the Lexical Superstition of Large Language Models for Code Comprehension: Re-evaluation on Code of Low Lexical Quality

arXiv:2609.26388v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in n

researcharxiv-cs-cl

On the Role of the Projector in Contrastive Self-Supervised Learning: Last-Layer Rank Dynamics Drive Representation Quality

arXiv:2609.26334v1 Announce Type: new Abstract: The dimensional collapse of representations in self-supervised contrastive learning is an ever-present issue. One notable technique to prevent such a co

One Domain, Many Tongues: Composing Domain and Language LoRAs for Cross-Lingual Remote-Sensing MLLMs without Paired Data

arXiv:2609.26097v1 Announce Type: new Abstract: Remote-sensing (RS) multimodal large language models (MLLMs) are trained and evaluated only in English, while text-only instruction data covers over 100

researcharxiv-cs-cl

One-Step Generative Surrogate Models via Block-Triangular Joint Drifting

arXiv:2609.26435v1 Announce Type: new Abstract: Drifting provides a direct route to one-step generative models, but applying it directly to stochastic transition modeling requires multiple samples of

open-webui and open-terminal thoughts

model-releasesr-localllama

I have been using open-webui and open-terminal. Open-terminal is installed in a VM and gives the agent a ton of control of it's own system that I keep away from my normal network. I find this gives th