Search: “research”

LLM-Grounded Dynamic Task Planning with Hierarchical Temporal Logic for Human-Aware Multi-Robot Handover

arXiv:2602.09472v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) enable non-experts to specify open-world multi-robot tasks, but the generated plans are often kinematically infea

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Local Ai

Local-first personal AI agent that runs on Ollama + Telegram — looking for feature ideas

DGX agent

I’ve been building ClawLite, an open-source personal AI assistant that talks to you through Telegram and defaults to Ollama (local models). What it does: Multi-agent research with actual cross-source

local-air-ollama

30 Jul 2026

LumaGuide: Distribution Shaping for Training-Free HDR Generation in Diffusion Models

arXiv:2607.26237v1 Announce Type: new Abstract: Pretrained diffusion models generate realistic images but are constrained by the statistical biases of their training data, limiting their ability to pr

MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization

arXiv:2607.26315v1 Announce Type: new Abstract: To operate effectively across diverse contexts, robots must not only perform manipulation tasks accurately but also adapt how their actions unfold to th

Hardware

NeoRacer: An Open, Standardized 1:12 Scale Autonomous Race Car for Benchmarking and Education

arXiv:2607.26855v1 Announce Type: new Abstract: Many scientific fields rely on standard benchmarks and shared platforms to improve review and reproducibility, but autonomous systems research still lac

hardwarearxiv-cs-ro

Neural Network Assisted Lifting Steps For Improved Fully Scalable Lossy Image Compression in JPEG 2000

arXiv:2403.01647v2 Announce Type: replace Abstract: This work proposes to augment the lifting steps of the conventional wavelet transform with additional neural network assisted lifting steps. These a

No Data Is Not No Risk: Visibility Aware Graph-Based Inference of Business Conduct Risk

arXiv:2607.26859v1 Announce Type: cross Abstract: The monitoring of business conduct risk is hindered by sparse, uneven, and visibility-biased data. Prior studies show that business conduct risk infor

On the Rademacher Complexity of Graph Neural Networks: Unifying Expressivity and Geometry

arXiv:2510.10101v4 Announce Type: replace Abstract: Understanding the interplay between generalization, expressivity, and the geometry of the input space is a central challenge in graph learning. The

On the robustness of noisy solutions in non-convex neural networks

arXiv:2607.27000v1 Announce Type: cross Abstract: Optimization in non-convex neural network models is strongly influenced by the geometry of the solution space: sparse, isolated, point-like clusters a

Safety

one of the top cybersecurity models, post-trained from open weights by @depthfirstlabs on @FireworksAI_HQ long-horizon RL is as much an infr…

one of the top cybersecurity models, post-trained from open weights by @depthfirstlabs on @FireworksAI_HQ long-horizon RL is as much an infra problem as a research one: 100+ turn rollouts, async/pipel

safetyfireworks-ai--x

Ontology-driven personalized information retrieval for XML documents

arXiv:2603.21139v2 Announce Type: replace-cross Abstract: This paper addresses the challenge of improving information retrieval from semi-structured eXtensible Markup Language (XML) documents. Traditi

Pangram 4 Technical Report

arXiv:2607.27183v1 Announce Type: new Abstract: We present Pangram 4, the latest deep-learning-based AI-text classification model from Pangram Labs. We achieve an AUROC of 0.9916 with a false positive

Particle-Filtering-based Latent Diffusion for Inverse Problems

arXiv:2408.13868v2 Announce Type: replace Abstract: Current strategies for solving image-based inverse problems apply latent diffusion models to perform posterior sampling.However, almost all approach

Physics-Informed Graph Neural Networks for Robust AC-Optimal Power Flow

arXiv:2410.04818v2 Announce Type: replace-cross Abstract: We present PINCO, an unsupervised learning framework that integrates Graph Neural Networks with physics-informed neural networks for AC optima

Physics-Informed Singular-Value Learning for Cross-Covariances Forecasting in Financial Markets

arXiv:2601.07687v3 Announce Type: replace-cross Abstract: Recent advances in nonlinear shrinkage yield asymptotically optimal cleaners for large covariance matrices and have been extended to empirical

PIKS: Universal Physics-Informed Kernel Methods

arXiv:2607.27062v1 Announce Type: cross Abstract: Physics-informed machine learning incorporates physical principles --often expressed via differential operators-- into data-driven models. While physi

Prior Directions: Why GUI Grounding Gets Locked in the Past

arXiv:2607.26913v1 Announce Type: new Abstract: Vision-language models often use descriptions of earlier visual states to make decisions about the current scene. When the scene changes, stale language

PRISM-Net: Patient-specific reference-guided inter-breast symmetry matching for three-class breast DCE-MRI classification

arXiv:2607.26799v1 Announce Type: new Abstract: Breast DCE-MRI AI is increasingly being explored for breast-level classification of no-lesion, benign, and malignant findings, beyond conventional lesio

RA-Det: Towards Universal Detection of AI-Generated Images via Robustness Asymmetry

arXiv:2603.01544v2 Announce Type: replace Abstract: Recent image generators produce photo-realistic content that undermines the reliability of downstream recognition systems. As visual appearance cues

Randomizing the Number of Centers in k-means++

arXiv:2607.26202v1 Announce Type: cross Abstract: The k-means++ algorithm is a standard and widely used seeding method for k-means clustering, but for a fixed number k of centers its worst-case expect

ReDiSC: A Reparameterized Masked Diffusion Model for Scalable Node Classification with Structured Predictions

arXiv:2507.14484v2 Announce Type: replace Abstract: In recent years, graph neural networks (GNN) have achieved unprecedented successes in node classification tasks. Although GNNs inherently encode spe

Registration-Grounded Spectral Fusion for Unregistered WLI/NBI Endoscopic Lesion Segmentation

arXiv:2607.26395v1 Announce Type: new Abstract: White-light imaging (WLI) and narrow-band imaging (NBI) provide complementary views of endoscopic lesions, but their paired observations are often spati

Reinforcement Learning on Cost-Constrained Quadrupedal Hardware

arXiv:2607.26434v1 Announce Type: new Abstract: Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the

Relation Geometry in Semantic Space of Language Models

arXiv:2607.26762v1 Announce Type: new Abstract: When it comes to generating vector representations of words, current language models are achieving high-quality results. However, what is not known is t

Representation Trajectories Matters: Complementary Evidence for OOD Detection and Image Classification

arXiv:2607.26565v1 Announce Type: new Abstract: Vision models do not form a representation at once; each block revises it. We ask whether the resulting computation path contains evidence that the fina

Revisiting Lossy Verification in Speculative Decoding: Mechanisms, Trade-offs, and Failure Modes

arXiv:2607.26627v1 Announce Type: new Abstract: Speculative Decoding (SD) accelerates large language model inference by allowing a lightweight draft model to propose tokens that are subsequently verif

Robust RPC Bundle Adjustment for Multi-Date Satellite Imagery with Season-Invariant Correspondences

arXiv:2607.26973v1 Announce Type: new Abstract: Accurate refinement of Rational Polynomial Camera (RPC) models is essential for high-quality satellite image geolocation. In ground control point (GCP)-

SceneExpander: Text-Guided 3D Scene Expansion via Free-Form View Insertion

arXiv:2603.27084v3 Announce Type: replace Abstract: World building with 3D scene representations is increasingly important for content creation, simulation, and interactive experiences, yet real workf

SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI

arXiv:2607.27139v1 Announce Type: new Abstract: Accurate 3D reconstruction from satellite imagery typically relies on near-simultaneous stereo pairs, limiting its applicability to diachronic settings

Sensor-Placement-Agnostic Sonomyography: Toward Continuous High-Dimensional Control by Users with Tetraplegia

arXiv:2607.26401v1 Announce Type: cross Abstract: Sonomyography (SMG) enables continuous device control via ultrasound-measured muscle deformation signals, but existing SMG interfaces generally requir

Shot-based quantum encoding: a data-loading paradigm for quantum neural networks

arXiv:2604.06135v2 Announce Type: replace-cross Abstract: Efficient data loading remains a bottleneck for near-term quantum machine learning. Existing schemes (angle, amplitude, and basis encoding) ei

Sim2Win: A Team-Agnostic, Event-Based Pre-Match Outcome Prediction and Tactical Profiling System for Football

arXiv:2607.26061v1 Announce Type: new Abstract: Pre-match tactical decision-making in professional football relies heavily on subjective expert analysis and identity-based scouting systems that cannot

Skillful forecasting of offshore winds from satellite scatterometer constellations

arXiv:2607.27152v1 Announce Type: new Abstract: Accurate intraday forecasts of offshore wind are becoming increasingly important for power system operation and the integration of growing shares of off

Sky sphere representation in language models

arXiv:2607.27092v1 Announce Type: new Abstract: We analyze whether language models of size ~100B have a representation of the night sky map that is decodable from their residual stream. We find that m

Spline-Based Boundary Representations for Sparse View Reconstruction and Simulation Using Isogeometric Analysis

arXiv:2607.26234v1 Announce Type: new Abstract: Image-based reconstruction aims to recover three-dimensional geometry from images. Recent advances have enabled the recovery of visually detailed models

SPROUT: A Scalable Diffusion Foundation Model for Agricultural Vision

arXiv:2603.27519v2 Announce Type: replace Abstract: Image-based plant phenotyping depends on dense structural understanding of crops, yet pixel-level annotation remains expensive across species, organ

Statistical laws and linguistics differ in naturalistic video and fictional conversations

arXiv:2512.18072v3 Announce Type: replace Abstract: Conversation is a cornerstone of social connection and is linked to well-being outcomes. Conversations vary widely in type with some portion generat

Step-Attention Refinement of DINOv3 Features for Efficient Anterior Eye Segmentation

arXiv:2607.27087v1 Announce Type: new Abstract: Anterior eye segment (AES) segmentation is a key component of both ocular biometrics and emerging clinical image analysis applications. However, heterog

StructureGS: Structure-aware Gaussian Splatting for Articulated Object Reconstruction

arXiv:2607.26889v1 Announce Type: cross Abstract: Reconstructing articulated objects with multiple movable parts is essential for understanding object structure and enabling physical interaction. Howe

The Download: tricking LLMs, and reviving geothermal plants

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. A fundamental flaw leaves LLMs strikingly vulnerable to attack

researchmit-tech-review

The Sparsity Ceiling: Where Spiking Networks Can and Cannot Trade Activity for Energy

arXiv:2607.26648v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are promoted as an energy-efficient substrate because sparse, event-driven activity replaces dense multiply-accumulates

Time-delay Control Using a New Nonlinear Adaptive Law for Cable-Driven Robots

arXiv:2607.26383v1 Announce Type: cross Abstract: Cable-driven manipulators exhibit strong nonlinearities and low structural stiffness, which make precise control challenging under time-varying uncert

TPD: Temporal Prior Decoupling for Text-to-Video Diffusion Models

arXiv:2607.26706v1 Announce Type: new Abstract: Text-to-video diffusion models generate temporally coherent content from natural language, yet when a prompt describes an early scene that persists whil

Understanding Context Sampling in TabPFN on Small Tabular Datasets

arXiv:2607.26628v1 Announce Type: new Abstract: TabPFN performs classification through in-context learning: it conditions on a set of labeled training rows (the context, or prototypes) and predicts te

Universality and Approximation Rates of Graph Neural Networks with Random Features

arXiv:2607.26699v1 Announce Type: new Abstract: We investigate message-passing graph neural networks with random node features. Random node features are known to enhance the expressiveness of graph ne

Using large language models to probe the limits of atom-centered structural descriptors

arXiv:2607.26984v1 Announce Type: cross Abstract: Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modelin

VideoNorms: Benchmarking Cultural Awareness of Video Language Models

arXiv:2510.08543v2 Announce Type: replace-cross Abstract: As Video Large Language Models (VideoLLMs) are deployed globally, it is important to assess their ability to reason across cultural contexts.

VidMap: Exploiting Temporal Structure for Video-Based Structure-from-Motion

arXiv:2607.27194v1 Announce Type: new Abstract: Accurately recovering the camera's calibration and metric poses for any unconstrained video would unlock large-scale training data for navigation and sc