Search: “models”

arXiv:2610.04544v1 Announce Type: cross Abstract: Many groups now delegate label ontology and metadata harmonization to agentic LLM pipelines. We built one and audited it. Our aggregate scores looked

agentsarxiv-cs-lg

Applications

Learning Granger Causality under Latent Confounding via Intervention-Induced Heterogeneity

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2510.19138v2 Announce Type: replace Abstract: Granger causality characterizes directed predictive dependencies in multivariate time series, but recovering such dependencies becomes challenging i

applicationsarxiv-cs-lg

6 Oct 2026

LeAVJEPA: A Minimalist Architecture for Audio-Visual Self-Supervised Learning

arXiv:2610.06226v1 Announce Type: cross Abstract: Prior audio-visual self-supervised learning methods rely on mechanisms such as EMA target encoders, prediction heads, reconstruction decoders, and con

safetyarxiv-cs-cv

Leveraging Cost-effective Robotics for K-12 STEM Education through Water Quality Monitoring Tasks

arXiv:2610.04565v1 Announce Type: new Abstract: Engaging K-12 students in authentic scientific research remains a significant challenge, particularly at the intersection of environmental science and r

local-aiarxiv-cs-ro

Local Fisher Information Enables Sparse Causal Discovery

arXiv:2610.04291v1 Announce Type: cross Abstract: Sparse causal discovery calls for methods that exploit graph structure without estimating high-dimensional densities. We introduce Fisher Information

Local2Mesh: Spatially Localized Contour-to-Mesh for Left Ventricular Reconstruction from Sparse 2D Cardiac MRI

arXiv:2610.06052v1 Announce Type: new Abstract: Three-dimensional (3D) left ventricular (LV) reconstruction from sparse cardiac magnetic resonance (CMR) imaging remains challenging due to inter-slice

safetyarxiv-cs-cv

Low-Fidelity FDM Spectral Guidance for Neural Eigenvalue Solvers

arXiv:2610.04695v1 Announce Type: new Abstract: Operator eigenvalue problems appear throughout science. Classical methods usually discretize the operator into a matrix and then solve the resulting mat

MarvisNav: Making Memory Visible on Route Choices for Zero-Shot Object Navigation

arXiv:2610.06510v1 Announce Type: new Abstract: When searching for an object, people choose their next move by considering both likely target locations and places already explored. The current view ca

safetyarxiv-cs-ro

Masked Privileged-Information Distillation for Multimodal Skin Lesion Classification Under Missing Clinical Metadata

arXiv:2610.03991v1 Announce Type: new Abstract: Multimodal skin lesion classification combines clinical images with patient metadata to improve diagnostic accuracy. However, complete metadata availabl

Hardware

MC-Sparse: Deconstructing and Closing the Dense-Sparse Attention Gap in Diffusion Transformers

arXiv:2610.06801v1 Announce Type: new Abstract: Sparse attention is a primary approach to reducing the latency of diffusion transformers in long-sequence generation tasks, such as video and high-resol

hardwarearxiv-cs-cv

MDKeyChunker: What Does One LLM Call per Chunk Buy for Markdown Retrieval?

arXiv:2603.23533v3 Announce Type: replace-cross Abstract: Markdown carries structure a parser reads for free: headers, section paths, and block boundaries. Many RAG pipelines also spend LLM calls per

MemPilot: Orchestrating On-Demand Multimodal Memory Curation for LLM Agents

arXiv:2610.06830v1 Announce Type: cross Abstract: Memory has become integral to the LLM agent ecosystem, supporting information retention and reuse across interactions. However, most existing agent me

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

local-aiarxiv-cs-lg

Mind the Drift: Diagonal Linear Networks Under Large Learning Rates

arXiv:2610.06120v1 Announce Type: new Abstract: Large learning rates can qualitatively change the trajectory of neural network training, often pushing optimization into regimes far from classical grad

Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injury

arXiv:2610.05552v1 Announce Type: new Abstract: Three-dimensional gait analysis guides rehabilitation after spinal cord injury but depends on marker-based motion capture and force plates, which few cl

Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data

arXiv:2610.06389v1 Announce Type: new Abstract: Super-resolution and semantic segmentation are known to benefit one another, especially in the Earth observation context. However, learning both tasks i

NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis

arXiv:2610.04722v1 Announce Type: new Abstract: Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, maki

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

local-aiarxiv-cs-ro

Optimal Oracle Complexity for Finite-Sum Monotone Inclusions

arXiv:2610.05038v1 Announce Type: cross Abstract: We present an oracle-optimal method for finite-sum monotone inclusions under mean-square Lipschitz continuity. Our switching regularization method fin

Optimizer Geometry Sets the Pace: Spectral Learning Dynamics in Matrix Factorization

arXiv:2610.04249v1 Announce Type: new Abstract: Recent successes of matrix- and curvature-based optimizers have renewed interest in how update geometry shapes learning. These methods normalize or prec

Order Matters: Competition-Guided Query Ordering for RNN-Based Object Detection

arXiv:2610.05191v1 Announce Type: new Abstract: DETR-style detectors use one-to-one bipartite matching during training to assign object queries to ground-truth objects, enabling end-to-end set predict

Tutorials

Out-of-control Hamiltonian Learning

arXiv:2610.06709v1 Announce Type: cross Abstract: Learning the Hamiltonian of a many-body system from its dynamics is a central task in quantum science, yet the algorithms with the strongest provable

tutorialsarxiv-cs-lg

Outcome-Guided On-Policy Self-Distillation

arXiv:2610.05070v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) provides denser token-level supervision and better computational efficiency than Reinforcement Learning with Verifiab

Agents

Pareto-Dominant Clarification: Post-Training Coding LLMs via PPO-Lagrangian Budget Constraints

arXiv:2610.04089v1 Announce Type: new Abstract: Coding agents operating under ambiguous instructions or user prompts must decide whether to ask clarifying questions or attempt a solution directly. Whi

agentsarxiv-cs-lg

Personal VAD: Speaker-Conditioned Voice Activity Detection

arXiv:1908.04284v5 Announce Type: replace-cross Abstract: In this paper, we propose 'personal VAD', a system to detect the voice activity of a target speaker at the frame level. This system is useful

local-aiarxiv-cs-lg

Physics is the Best Teacher: Consistency Learning for Time-Invariant Operators of Chaotic Dynamics

arXiv:2610.04108v1 Announce Type: new Abstract: Accelerating the prediction of long-term behavior in chaotic systems is crucial in scientific computing. However, existing methods rely on numerical sol

PlatoLTL: Scaling LTL-Guided Multi-Task RL

arXiv:2601.22891v3 Announce Type: replace Abstract: Linear temporal logic (LTL) has emerged as a powerful formalism for specifying structured, temporally extended tasks in multi-task reinforcement lea

Poisson-GENERIC Neural Operators: Exact Metriplectic Structure in Function Space via Casimir Entropies

arXiv:2610.05570v1 Announce Type: new Abstract: Existing thermodynamically consistent neural operators impose the GENERIC degeneracy conditions by projecting the reversible operator onto the complemen

Polynomial neural surrogates for designing photonic quantum experiments

arXiv:2610.06032v1 Announce Type: cross Abstract: Physics simulators can support the discovery of quantum experiments by predicting the states generated by experimental configurations. When these simu

Prompt Dominance and Asymmetric Verifier Costs: Empirical Ablations of GRPO at 1B Scale on GSM8K

arXiv:2610.04928v1 Announce Type: new Abstract: This paper studies GRPO at 1B scale from both directions: what estimator choices do to the learning signal, and what a degraded reward signal does to wh

RAGrasp: Geometry-Semantic Template Retrieval and Grasp Transfer

arXiv:2610.04438v1 Announce Type: cross Abstract: We present RAGrasp, a retrieval-augmented pipeline for planar parallel-jaw grasping from a compact set of locally collected, grasp-annotated RGB-D (co

local-aiarxiv-cs-ro

Ramp Metering Control via Hybrid State Deep Reinforcement Learning in Partially Observable Connected Vehicle Environments

arXiv:2610.06266v1 Announce Type: new Abstract: Freeway on-ramp merges are major sources of congestion, causing significant economic and environmental costs. While Deep Reinforcement Learning (DRL) of

Referring Multi-Object Tracking in Moving-Camera Videos via Global Motion Compensation

arXiv:2610.04185v1 Announce Type: new Abstract: Referring multi-object tracking (RMOT) takes a video and a language expression as input and tracks all referred objects. Many tracking requirements invo

Relational Synthesis: Structure-Mediated Concatenative Synthesis for Foley and Retrieval-Augmented Audio Generation

arXiv:2610.05768v1 Announce Type: cross Abstract: We ask: given a retrieved source audio S and a separate reference audio R, can we synthesize novel audio Y out of this pair (S,R) such that Y remains

Residual Visual Credit Optimization: Conserved Evidence Routing for Multimodal Reinforcement Learning

arXiv:2610.04918v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards scales multimodal reasoning, but an outcome reward says how much a trajectory is worth, not how that valu

local-aiarxiv-cs-lg

Revealing After Overwriting: An Exponential POMDP OPE Lower Bound under History-Dependent Logging

arXiv:2610.05063v1 Announce Type: new Abstract: Multi-step revealing can make off-policy evaluation tractable under memoryless logging. With history-dependent logging, state decodability and target-re

Robot Learning with Visual Predicted Force

arXiv:2610.04741v1 Announce Type: new Abstract: Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through

safetyarxiv-cs-ro

Robust Local Optimization Done Right

arXiv:2610.05743v1 Announce Type: new Abstract: RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement.

local-aiarxiv-cs-cv

Robust Tensor Completion via Reflective Convolution Nuclear Norm Minimization

arXiv:2610.04979v1 Announce Type: new Abstract: Robust tensor completion recovers multidimensional data from partial observations corrupted by sparse gross errors. Existing convolutional low-rank mode

Tutorials

S^3N: A Spherical Spiral Scanning Network for Weather Forecasting

arXiv:2610.04338v1 Announce Type: new Abstract: Machine learning-based weather prediction (MLWP) has achieved strong performance in global weather forecasting. Recent Hierarchical Equal Area isoLatitu

tutorialsarxiv-cs-lg

Scalable Minimal-Change Learning for Controllable Image Editing

arXiv:2610.06021v1 Announce Type: new Abstract: Image editing should change only the attributes specified by an instruction while preserving everything else, yet current methods often make unintended

local-aiarxiv-cs-cv

Selecting Long-Horizon Trajectories for Reliable and Efficient Terminal-Agent Training

arXiv:2610.05831v1 Announce Type: new Abstract: Terminal agents are commonly trained by imitating long teacher trajectories, yet how much of each trajectory to supervise remains unexplored. We study t

Shadow Feature Refinement Network: Progressive Feature Refinement based on Knowledge Distillation for Effective Shadow Removal

arXiv:2610.05325v1 Announce Type: new Abstract: In the field of deep learning, has seen significant advancements; however, shadow removal remains a persistent challenge owing to the variable sizes and

Agents

SPACE-CLIP: Spatial Perception via Adaptive CLIP Embeddings for Monocular Depth Estimation

arXiv:2601.17657v4 Announce Type: replace Abstract: Robotic and autonomous systems need dense spatial cues, yet adding a dedicated depth estimator can duplicate visual processing already performed by

agentsarxiv-cs-cv

Sparse Calibration-Based Personalization of Kernel-Based Gait Phase and Speed Estimation Using Wearable IMUs

arXiv:2610.03931v1 Announce Type: new Abstract: This paper presents sparse calibration-based personalization for kernel-based gait phase and walking speed co-estimation from wearable inertial measurem

researcharxiv-cs-ro

Spontaneous morning chat with Juergen Schmidhuber and Jake Newfield philosophizing about AI. Sry my mic somehow disconnected but Juergen had…

researchsebastian-raschka--x

Spontaneous morning chat with Juergen Schmidhuber and Jake Newfield philosophizing about AI. Sry my mic somehow disconnected but Juergen had the more interesting points anyways! Our CEO @Jake_Newfield

Stability and Generalization of Stochastic Nonconvex Optimization under Heavy-Tailed Noise: From Gradient Norm to Goldstein Stationarity

arXiv:2601.19730v2 Announce Type: replace Abstract: The empirical evidence indicates that stochastic optimization with heavy-tailed gradient noise is more appropriate to characterize the training of m

Stability-Shaped Deep Graph Learning

arXiv:2610.06344v1 Announce Type: new Abstract: In deep graph neural networks, increasing depth enlarges the receptive field but often leads to over-smoothing, where node representations tend to align