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Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing

arXiv:2606.31230v1 Announce Type: new Abstract: We study the task of learning the structure of a d-sparse Gaussian graphical model on n variables from a single trajectory of Glauber dynamics. Beyond a

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Learning to Select, Not Relearn: Hard-Routed Mixtures of Reasoning LoRAs

DGX agent

arXiv:2606.31413v1 Announce Type: new Abstract: Composing independently trained LoRA adapters into a single large language model is useful for multi-domain adaptation, especially when the original tra

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1 Jul 2026

LeCropFollow: Latent Space Planning for Navigation in Unstructured Crop Fields

arXiv:2606.31941v1 Announce Type: cross Abstract: Unstructured navigational features, such as irregular planting or discontinuities, remain the primary failure mode for under-canopy agricultural robot

LeWorld model becomes ADAPTIVE and meets MODEL-PREDICTIVE CONTROL AdaJEPA by Yann LeCun and colleagues performs actions, then checks the pre…

LeWorld model becomes ADAPTIVE and meets MODEL-PREDICTIVE CONTROL AdaJEPA by Yann LeCun and colleagues performs actions, then checks the predicted latent state versus the observed and adapts at TEST T

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Linguistic Distancing on Social Media: Indicators of Emotion Regulation Across Age Groups

arXiv:2606.30957v1 Announce Type: new Abstract: Managing our emotional responses to events is key to emotional well-being, a process referred to as emotion regulation in psychology. Previous work has

Listening Between the Lines: Joint Learning of ASR Embeddings and LLM-Augmented Linguistics for Dementia Detection

arXiv:2606.30675v1 Announce Type: cross Abstract: Early detection of dementia through speech analysis offers a non-invasive screening alternative, but capturing both acoustic and linguistic biomarkers

LiteMatch: Lightweight Zero-Shot Stereo Matching via Cost Volume Stabilization

arXiv:2606.31636v1 Announce Type: new Abstract: Despite rapid progress in learning-based stereo matching, high accuracy is often achieved at the cost of heavy backbones and computationally intensive 3

LLM-Powered Interactive Robotic Action Synthesis from Multimodal Speech, Gestures, and Music

arXiv:2606.31158v1 Announce Type: cross Abstract: The quest for intuitive and natural human-robot interaction (HRI) remains a significant challenge in robotics. Traditional methods often rely on rigid

Local Pheromone Network: Sparse Local Learning with Multi-Scale Synaptic Trails, Consolidation, and Replay

arXiv:2606.30669v1 Announce Type: cross Abstract: Backpropagation-trained dense neural networks are powerful function approximators, but they couple learning across many parameters and can overwrite p

Localized Conformal Prediction for Image Classification with Vision-Language Models

arXiv:2606.31577v1 Announce Type: new Abstract: Conformal predictions have attracted significant attention in the field of uncertainty quantification, mainly because of their strong marginal coverage

LUMOS: A Semantic Operating-System Layer for Accessibility-Grounded AI Agents

arXiv:2606.30697v1 Announce Type: cross Abstract: Current operating systems expose interfaces optimized for human users but not for AI agents. Humans benefit from pixels, icons, windows, visual groupi

Machine Learning-based Feedback Linearization Control of Quadrotor Subject to Unmodeled Dynamics

arXiv:2606.31199v1 Announce Type: cross Abstract: The control of agile quadrotors in dynamic and uncertain environments remains an open area of investigation to this day, particularly when the complet

Making Sense of Touch from the Child's View for Contrastive Learning

arXiv:2606.31943v1 Announce Type: new Abstract: Is the sense of touch a mechanism for human babies' learning of visual concepts? If so, can we quantify its importance, and to what extent do babies rel

Mantis: Lightweight Foundation Model for Time Series Classification

arXiv:2502.15637v2 Announce Type: replace-cross Abstract: While foundation models have revolutionized various domains, their application to time series classification remains rather under-explored, wi

MAPE: Defending Against Transferable Adversarial Attacks Using Multi-Source Adversarial Perturbations Elimination

arXiv:2606.31378v1 Announce Type: new Abstract: Neural networks are vulnerable to meticulously crafted adversarial examples, leading to high-confidence misclassifications in image classification tasks

Mean-Field Model for Two-Layer Neural Networks Trained with Consensus-Based Optimization

arXiv:2511.21466v3 Announce Type: replace Abstract: We study Consensus-Based Optimization (CBO) for two-layer neural network training. We compare the performance of CBO against Adam on two test cases

Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments

arXiv:2606.30987v1 Announce Type: new Abstract: Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Foreca

MediEncoder: Nonlinear Representation Learning for High-Dimensional Causal Mediation Analysis

arXiv:2606.30648v1 Announce Type: cross Abstract: Causal mediation analysis decomposes a treatment effect into indirect pathways through mediators and direct pathways not operating through them. Moder

Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation

arXiv:2606.31777v1 Announce Type: new Abstract: Autoregressive (AR) modeling has recently achieved remarkable progress in native 3D mesh generation, largely due to its natural ability to handle variab

Minimizing Quantized Semantic Age of Information (QSAoI) in Foundation Model-Based Semantic Communications

arXiv:2606.31303v1 Announce Type: cross Abstract: The emerging techniques of semantic communications and edge computing in 6G networks necessitate a paradigm shift toward co-designed semantic-aware an

Mitigating Positional Leakage in 3D Masked Autoencoders for Robust Representation Learning

arXiv:2606.31570v1 Announce Type: cross Abstract: Masked autoencoding has emerged as a prominent paradigm for self-supervised learning on 3D point clouds, achieving competitive performance across down

Modal CEGAR-tableaux with RECAR and resolution-based SAT-shortcuts

arXiv:2606.31878v1 Announce Type: cross Abstract: We investigate two approaches for extending CEGAR-tableaux with SAT-shortcuts using a previously known approach called RECAR but also a totally new ap

MS-Resampler: Multi-Scope Visual Resampling for Efficient Multimodal LLMs

arXiv:2606.31383v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) typically employ resampling-based projectors to transform dense visual features into a compact token sequence f

MSNN-LINet: Cross-Modal Learning via Continuous Linear Integration

arXiv:2606.31135v1 Announce Type: new Abstract: We present LINet (Linear Integration Network), a Multi-Stream Neural Network (MSNN) for RGB-D scene classification. Current multi-modal architectures tr

Multi-Channel Uncertainty-Weighted Score Matching for Conditional Diffusion in Medical UDA

arXiv:2509.22476v2 Announce Type: replace Abstract: Robust medical image segmentation across modalities remains challenging due to severe domain shifts and the lack of target-domain labels. While diff

Multilingual Polarization Detection Using Transformer-Based Models with Class Weighting and Threshold Tuning

arXiv:2606.30857v1 Announce Type: new Abstract: This paper describes our submission to SemEval-2026 Task 9 on detecting multilingual, multicultural, and multievent online polarization. We address all

Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again

arXiv:2606.30995v1 Announce Type: new Abstract: Recent work has shown that well-optimized individual decision trees can match complex black box models in some settings, primarily in noisy domains. For

MV-GEL: Language-Driven Multi-View Geometric Entity Localization on Meshes

arXiv:2606.31533v1 Announce Type: new Abstract: Identifying and grounding precise geometric entities, such as edges, planar regions, and curved surfaces within 3D objects, is foundational to computer-

Neuro-Bayesian-Symbolic Residual Attention Shallow Network: Explainable Deep Learning for Cybersecurity Risk Assessment

arXiv:2606.30953v1 Announce Type: new Abstract: We introduce the Neuro-Bayesian-Symbolic Residual Attention Shallow Network (NBS-RASN), a hybrid neural architecture for explainable cybersecurity risk

No Prompt, No Leaks: A Robust Generative Steganography Framework via Prompt-Free Diffusion

arXiv:2606.31427v1 Announce Type: new Abstract: Generative image steganography synthesizes stego images directly from secret information to achieve inherent security advantages. Latent Diffusion Model

Not Every Time and Frequency Need to Be Forgotten in Diffusion Unlearning

arXiv:2510.17917v2 Announce Type: replace-cross Abstract: Data unlearning aims to remove the influence of specific training samples from a trained model. In fine-tuning methods, data unlearning relies

On the pod: 'Constrained Adaptive Rejection Sampling' with @ucsd_cse professor @lorisdanto. Hear how symbolic AI experts have navigated the …

researchfrancois-chollet--x

On the pod: 'Constrained Adaptive Rejection Sampling' with @ucsd_cse professor @lorisdanto. Hear how symbolic AI experts have navigated the LLM era and why the future of AI code generation depends on

On the Role of Rotation Equivariance in Monocular 2D-to-3D Human Pose Lifting

arXiv:2601.13913v2 Announce Type: replace Abstract: Estimating 3D from 2D is one of the central tasks in computer vision. In this work, we consider the monocular setting, i.e. single-view input, for 3

Online TT-ALS for Streaming Tensor Decomposition with Incremental Orthogonalization

arXiv:2606.31061v1 Announce Type: cross Abstract: Tensor Train (TT) decomposition is a powerful technique for analyzing high-dimensional data. Existing algorithms for computing TT decompositions can b

Optimal Self-Consistency for Efficient Reasoning with Large Language Models

arXiv:2511.12309v2 Announce Type: replace-cross Abstract: Self-consistency (SC) is a widely used test-time inference technique for improving performance in chain-of-thought reasoning. It consists of g

Overview of the TalentCLEF 2026: Skill and Job Title Intelligence for Human Capital Management

arXiv:2606.31692v1 Announce Type: new Abstract: This paper presents an overview of the second edition of the TalentCLEF challenge, organized as a Lab at the Conference and Labs of the Evaluation Forum

Pano3D: Unified 3D Reconstruction and Panoptic Segmentation

arXiv:2606.14307v2 Announce Type: replace Abstract: Recent advances in 3D feedforward reconstruction neural networks have achieved remarkable success in dense reconstruction from images without any ca

Patch-PODiff-ViT: Structured Latent Diffusion with Patchwise POD for Super-Resolution and Uncertainty Quantification

arXiv:2606.31290v1 Announce Type: new Abstract: Diffusion models enable probabilistic super-resolution and conditional generation, but pixel-space methods are computationally expensive and learned lat

Patient-Level Elbow Abnormality Detection: Leakage-Aware Evaluation of Learned Preprocessing, Calibration, and Triage-Oriented Operating Points

arXiv:2606.31348v1 Announce Type: new Abstract: In this study, we examine learned preprocessing pipelines in the context of triage-oriented orthopedic abnormality detection task using elbow radiograph

PGUDA: Pressure-Guided Unsupervised Domain Adaptation with Cross-Modal Knowledge Distillation for sEMG-Based Gesture Recognition

arXiv:2606.31349v1 Announce Type: cross Abstract: Surface electromyography (sEMG)-based gesture recognition has emerged as a promising technology for natural human-computer interaction. However, its p

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer

arXiv:2511.19778v2 Announce Type: replace Abstract: Rotary positional embeddings (RoPE) are widely used in diffusion transformers (DiTs) to encode spatial relationships, yet their behavior with mixed-

{Phi}eat: Physically Grounded Material Feature Representation

arXiv:2511.11270v2 Announce Type: replace Abstract: While foundation models have emerged as general-purpose visual backbones, their representations are primarily optimized for semantics and lack expli

PhotoQuilt: Training-Free Arbitrary-Resolution Photomosaics via Bootstrapped Tiled Denoising

arXiv:2606.30968v1 Announce Type: new Abstract: Photomosaics are large images whose local regions are seen as independent tiles while their overall arrangement forms a coherent scene. Generating them

Physics-informed Conditional Normalizing Flows for Angles-only Cislunar Orbit Determination

arXiv:2606.30936v1 Announce Type: cross Abstract: Generative Astrodynamics is advanced in this work by extending generative modelling to an orbit determination problem in the cislunar environment. The

Ponder This Challenge - July 2026 - Return of the Superheroes

IBM's July 2026 Ponder This Challenge likely presents a mathematical or logic puzzle with a superhero theme, continuing IBM Research's monthly series of recreational problem-solving challenges. The pu

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PoseGravity: Pose Estimation from Points and Lines with Axis Prior

arXiv:2405.12646v3 Announce Type: replace Abstract: This paper presents a new algorithm to estimate absolute camera pose given an axis of the camera's rotation matrix. Current algorithms solve the pro

Practical High-Fidelity Novel-View Synthesis of Mounted Lepidoptera

arXiv:2606.31679v1 Announce Type: cross Abstract: Mounted butterflies are among the most striking objects in natural history collections. However, their beauty is notoriously hard to digitize in 3D: t

President Donald Trump’s administration wants to enlist the public in attacking what it sees as wasteful spending. https://scim.ag/4v5vkie

President Trump's administration is launching a public campaign to identify and eliminate what it considers wasteful government spending. The initiative aims to engage citizens in efforts to reduce pe

researchyann-lecun--x