Search: “research”

Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents

arXiv:2606.30306v1 Announce Type: cross Abstract: Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions. We treat them as persistent-state

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An Integrated Two-Stage Deep-Learning Tool for Rapid Post-Hurricane Damage Identification and Repair Scheduling

DGX agent

arXiv:2606.29117v1 Announce Type: cross Abstract: Post-hurricane damage assessment and repair scheduling can require computationally intensive simulation and optimization. This paper presents an integ

researcharxiv-cs-lg

30 Jun 2026

An Overview of Formulae for the Higher-Order Kinematics of Lower-Pair Chains with Applications in Robotics and Mechanism Theory

arXiv:2309.05055v2 Announce Type: replace Abstract: The motions of mechanisms can be described in terms of screw coordinates by means of an exponential mapping. The product of exponentials (POE) descr

researcharxiv-cs-ro

Anatomy-Grounded Synthetic Coronary Angiography for Geometry-Informed Multi-View Matching

arXiv:2606.28474v1 Announce Type: cross Abstract: Accurate correspondence matching across multiple angiographic views is the prerequisite for 3D coronary reconstruction and interventional guidance. Ho

AnTenA: Actionable and Explainable Tensor Analysis System with Large Language Models

arXiv:2606.28708v1 Announce Type: new Abstract: Accurately explaining hidden patterns in multi-aspect data has typically been done by leveraging labels and/or accompanying auxiliary metadata. However,

researcharxiv-cs-cl

ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data

arXiv:2408.16028v4 Announce Type: replace-cross Abstract: Supervised-learning-based vulnerability detectors often fall short due to limited labelled training data. In contrast, Large Language Models (

Arbitrary Reduction of Validation Error for AI Decision Tests using Homomorphic AI and Repetition Codes

arXiv:2606.28994v1 Announce Type: cross Abstract: This paper presents new results and breakthrough obtained with the HbHAI techniques (Hash-based Homomorphic Artificial Intelligence) proposed in ite{f

ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matching

arXiv:2509.15942v3 Announce Type: replace-cross Abstract: Internal variability is a dominant contributor to the uncertainty of predictions at the interannual to decadal timescale. A typical approach t

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization

arXiv:2510.06732v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small,

As a European, I don't understand how the sitting U.S. president—who has to pay $5 million to a woman he r@ped and defamed—can remain in off…

I can't provide a summary of this post without access to its actual content. The title appears to reference legal judgments involving a U.S. president, but I would need to verify the specific claims a

researchyann-lecun--x

AsyncMDE: Real-Time Monocular Depth Estimation via Asynchronous Spatial Memory

arXiv:2603.10438v2 Announce Type: replace-cross Abstract: Foundation-model-based monocular depth estimation offers a viable alternative to active sensors for robot perception, yet its computational co

Atompack: A Storage and Distribution Layer for Read-Heavy Atomistic ML Training Datasets

arXiv:2606.29975v1 Announce Type: new Abstract: Atomistic machine learning datasets are increasingly used for training: large immutable snapshots are read repeatedly, shuffled across epochs, staged ac

AUSLUN: A Fixed-Hover UAV--USV System for GNSS-Denied Maritime Search and Navigation

arXiv:2606.29875v1 Announce Type: new Abstract: Global navigation satellite system (GNSS) denial can prevent an unmanned surface vehicle (USV) from both finding a distant vessel and maintaining a glob

researcharxiv-cs-ro

Agents

Automated Quality Assessment of Geospatial Vector Data: A GeoAI Approach using Spatial Representation Learning

arXiv:2606.28390v1 Announce Type: cross Abstract: Geospatial vector data quality is a foundational research topic in GIS, yet classic rule-based quality assessment algorithms often struggle with diver

agentsarxiv-cs-ai

Automatic Extraction of Road Networks by using Teacher-Student Adaptive Structural Deep Belief Network and Its Application to Landslide Disaster

arXiv:2511.05567v2 Announce Type: replace-cross Abstract: An adaptive structural learning method of Restricted Boltzmann Machine (RBM) and Deep Belief Network (DBN) has been developed as one of promin

B3O: Scalable Boltzmann Batch Bayesian Optimization

arXiv:2606.30228v1 Announce Type: new Abstract: Modern engineering workflows increasingly rely on massive parallel simulation, driving the need for scalable, large-batch Bayesian Optimization (BO). Ex

Beyond Correlation: Learning Supervised, Sample-Distinct, and Eigenimage-Interpretable Representations

arXiv:2507.21136v2 Announce Type: replace-cross Abstract: Conventional dimensionality reduction methods mainly optimize variance or correlation, leaving statistical dependence, data diversity, contras

Beyond Point Estimates for Glaucoma Visual Field Forecasting with Diffusion Models

arXiv:2606.30417v1 Announce Type: cross Abstract: Forecasting visual fields (VFs) is critical for personalized monitoring and treatment planning in glaucoma. This is inherently uncertain due to hetero

Bidirectional Autoregressive Latent Diffusion for Forward and Inverse Magnetohydrodynamics

arXiv:2606.29620v1 Announce Type: cross Abstract: This work presents a new bidirectional autoregressive latent diffusion approach for predicting the evolution of multiple fields (mass density, pressur

Bit-ViP: Leveraging Bit-planes to Preserve Visual Privacy in Images through Obfuscation

arXiv:2606.29417v1 Announce Type: new Abstract: The unprecedented growth of computer vision applications, such as surveillance systems and social media, raises security and visual privacy concerns, es

BLUE: A Stale-Pixel Optical-Flow Compositor for Entropy-Efficient Surveillance Video Encoding

arXiv:2606.28753v1 Announce Type: cross Abstract: Continuous-recording surveillance systems face a storage problem that codec tuning alone cannot fully solve: even at aggressive CRF settings, a static

BrainRiem: Riemannian Prototype Learning for Source-Free Cross-Site Brain Network Diagnosis

arXiv:2606.29200v1 Announce Type: new Abstract: Multi-site functional MRI (fMRI) studies are essential for robust neuropsychiatric diagnosis yet suffer severe domain shifts from scanner heterogeneity,

BREIT: A Framework for Brain Stroke Reconstruction using Multi-Frequency 3D EIT

arXiv:2606.28787v1 Announce Type: cross Abstract: Multi-Frequency Electrical Impedance Tomography (MF-EIT) is a non-invasive, low-cost modality that reconstructs electrical property distributions from

Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding

arXiv:2606.29845v1 Announce Type: new Abstract: Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured

Brownian Bridge Diffusion-Based Joint Channel Estimation and Data Detection for Jamming-Resilient Receivers

arXiv:2606.28778v1 Announce Type: cross Abstract: In next-generation wireless networks, the growing density of devices and limited spectrum resources pose severe jamming challenges to fragile legitima

Model Releases

Building voice agents can come with tradeoffs. 💬 Better convos w/ speech to speech models Vs 🥪 More reliable harnesses w/ sandwich archite…

model-releasesharrison-chase--x

Building voice agents can come with tradeoffs. 💬 Better convos w/ speech to speech models Vs 🥪 More reliable harnesses w/ sandwich architecture How to build a voice research agent with both: ✅ Gemini

C^{2}R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders

arXiv:2606.30609v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) are widely used to interpret large language models by decomposing activations into sparse, human-understandable features, b

Can LLMs Rank? A Tale of Triads and Triage

arXiv:2606.30412v1 Announce Type: cross Abstract: From housing allocation for households experiencing homelessness to triage in emergency departments, LLMs are increasingly being considered as judges

Can regularization based JEPA (e.g. SIGReg) scale and compete with SOTA foundation models (DINO)? Here is the answer: yes and with 10x less …

Can regularization based JEPA (e.g. SIGReg) scale and compete with SOTA foundation models (DINO)? Here is the answer: yes and with 10x less data. VISReg (slight variation of SIGReg) competes with DINO

researchyann-lecun--x

CAN We Trust Your Results? A Cross-Dataset Study of Automotive IDS Evaluation

arXiv:2606.30430v1 Announce Type: cross Abstract: The increasing connectivity of modern vehicles has made securing in-vehicle communication networks a critical challenge. Intrusion Detection Systems (

Categorize Early, Integrate Late: Divergent Processing Strategies in Automatic Speech Recognition

arXiv:2601.06972v2 Announce Type: replace Abstract: In speech language modeling, two architectures dominate the frontier: the Transformer and the Conformer. However, it remains unknown whether their c

researcharxiv-cs-cl

CellDETR: A Detection-Guided Framework for Scalable Cell Representation Learning from Histopathology Images

arXiv:2606.29463v1 Announce Type: new Abstract: Recent advances in pathology foundation models have substantially improved patch and slide level representation learning from whole-slide images (WSIs).

Chamber geometry and specification numbers of Boolean threshold functions

arXiv:2606.29477v1 Announce Type: cross Abstract: The specification number sigma_n(f) of a Boolean threshold function f on n variables is the least number of points whose f-values determine f uniquely

Child-Centric Voice Anonymization in Single and Multi-Speaker Speech via Domain-Adapted SSL Models

arXiv:2606.29897v1 Announce Type: cross Abstract: Voice anonymization aims to protect speaker identity while preserving linguistic content and speech usability. However, most anonymization systems are

CLIMP: Contrastive Language-Image Mamba Pretraining

arXiv:2601.06891v2 Announce Type: replace Abstract: Contrastive Language-Image Pre-training (CLIP) relies on Vision Transformers whose attention mechanism is susceptible to spurious correlations, and

Clinical Reasoning Graphs: Structured Evaluation of LLM Diagnostic Reasoning Reveals Competence Without Consistency

arXiv:2606.29876v1 Announce Type: cross Abstract: Modern large language models (LLMs) reach 60-70% diagnostic accuracy on complex clinical case benchmarks, but accuracy alone cannot distinguish stable

Clinical Risk-Aware Multi-Level Grading for Coronary Artery Stenosis through Curved Feature Reconstruction

arXiv:2606.30082v1 Announce Type: new Abstract: Developing a multi-level grading model for coronary artery stenosis holds great clinical significance for the diagnosis of coronary artery disease. Howe

CLMASP: Coupling Large Language Models with Answer Set Programming for Robotic Task Planning

arXiv:2406.03367v2 Announce Type: replace Abstract: Large Language Models (LLMs) possess extensive foundational knowledge and moderate reasoning abilities, making them suitable for general task planni

Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks

arXiv:2606.28662v1 Announce Type: cross Abstract: The flatness hypothesis suggests that flatness of the loss landscape, as measured by the eigenvalues of the loss Hessian, correlates with better neura

Clustering with Non-adaptive Subset Queries

arXiv:2409.10908v3 Announce Type: replace-cross Abstract: Recovering the underlying k-clustering of a set U of n points by asking pair-wise same-cluster queries has garnered significant interest in th

CMSL: Constructive Multi-Sequence Learning for Recommendation Systems

arXiv:2606.28533v1 Announce Type: cross Abstract: Sequence learning has emerged as the promising paradigm in recommendation systems, surpassing traditional Deep Learning Recommendation Models (DLRM) b

CoLR-Det: Collaborative Latent Restoration for Small Object Detection in Low-Resolution Remote Sensing Images

arXiv:2601.12507v2 Announce Type: replace Abstract: Low-resolution remote sensing small object detection is limited by both missing visual details and the ambiguity of how details serve detection. Exi

COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models

arXiv:2606.28696v1 Announce Type: new Abstract: Composition is a high-level visual intent that governs where subjects are placed and how a scene is organized, yet current unified multimodal models rem

Complete virtual unwrapping and reading of a rolled Herculaneum papyrus

arXiv:2606.29085v1 Announce Type: cross Abstract: The carbonized papyri from Herculaneum preserve the only large-scale library to survive from classical antiquity, but many unopened rolls remain unrea

Concentration bounds on response-based vector embeddings of black-box generative models

arXiv:2511.08307v2 Announce Type: replace-cross Abstract: Generative models, such as large language models or text-to-image diffusion models, can generate relevant responses to user-given queries. Res

Conformal Prediction with Macro-Coverage Guarantees

arXiv:2606.28598v1 Announce Type: cross Abstract: Prediction sets should have high coverage to be useful, but some coverage notions are more practically relevant than others. In the classification set

Contact-Anchored Proprioceptive Odometry for Legged and Wheel-Legged Robots

arXiv:2602.17393v3 Announce Type: replace Abstract: Reliable odometry for legged robots without cameras or LiDAR remains challenging due to IMU drift and noisy joint velocity sensing. This paper prese

researcharxiv-cs-ro

Convergence of Continual Learning in Homogeneous Deep Networks

arXiv:2606.30559v1 Announce Type: new Abstract: We characterize weakly regularized continual classification in homogeneous models as sequential projections onto task margin sets. This result generaliz