Search: “research”

A Sobel-Gradient MLP Baseline for Handwritten Character Recognition

arXiv:2508.11902v4 Announce Type: replace Abstract: This study examines how much handwritten-character information is retained by a deliberately simple first-order edge representation. Instead of lear

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

A Two-Stage Cascade for Near-Real-Time Forest Anomaly Detection from Sentinel-1 SAR Time Series

DGX agent

arXiv:2610.02763v1 Announce Type: new Abstract: Tropical forest monitoring is essential for global climate stability and biodiversity preservation. To address the urgent need for rapid, reliable detec

researcharxiv-cs-lg

5 Oct 2026

Accurate Open-Loop Control of a Soft Continuum Robot Using Visually Learned Latent Dynamics

arXiv:2603.19655v2 Announce Type: replace Abstract: This work addresses open-loop control of a soft continuum robot (SCR) from video-learned latent dynamics. Visual Oscillator Networks (VONs) from pre

researcharxiv-cs-ro

Adaptive Second-Order Solvers for Fast Stochastic Diffusion Sampling

arXiv:2610.03034v1 Announce Type: cross Abstract: Diffusion models rely on numerical solvers requiring time-discretization, which has a large influence on the tradeoff between sampling cost and qualit

AIBL: Augmented Instance-Based Learning with Structured Memory and Neural Embeddings

arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over

AMBER: Multi-View Adaptive Budget Allocation for Listwise Vision-Language Reranking

arXiv:2610.02831v1 Announce Type: new Abstract: Vision-language models (VLMs) are powerful listwise rerankers for multimodal retrieval, but high inference costs restrict them to evaluating small local

Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models

arXiv:2610.03647v1 Announce Type: cross Abstract: Many machine learning methods aim to approximate the lower-dimensional manifold on which the data lives. A desirable feature of such methods is that t

An AI-Based Multi-Stage Approach for Androgenetic Alopecia Assessment from Low-Magnification Scalp Images

arXiv:2610.02421v1 Announce Type: new Abstract: Androgenetic alopecia (AGA) is characterized by patterned follicular miniaturization, increased single-hair follicular units, and altered hair-shaft dia

ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling

arXiv:2602.09009v2 Announce Type: replace-cross Abstract: Scaling network depth has been a central driver behind the success of modern foundation models, yet recent investigations suggest that deep la

Answering clinicians' questions over trial evidence tables with verifiable, feedback-driven language models

arXiv:2610.02576v1 Announce Type: new Abstract: Systematic reviews condense clinical trials into evidence tables, yet clinicians can interrogate these tables only through database queries, and many qu

Approximation Property of Dropout Neural Networks: Sobolev Rates and Confidence Bounds

arXiv:2610.02253v1 Announce Type: new Abstract: The universal approximation property of dropout neural networks does not by itself describe the network size required for an accurate random realization

AREX: Affine-Residual Exponential Integrator for Few-Step Sampling in Flow Matching

arXiv:2610.03483v1 Announce Type: cross Abstract: We introduce AREX, a training-free sampler for pretrained flow matching models that uses the target mean and covariance to capture an analytically tra

Asymptotic Performance of Time-Varying Bayesian Optimization

arXiv:2505.13012v3 Announce Type: replace-cross Abstract: Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying black-box objective function that may be noisy

Author Representation Strategies for Zero-Shot Authorship Attribution: A Comparative Study of LLM-Based and Embedding-Based Approaches

arXiv:2610.03531v1 Announce Type: new Abstract: Authorship Attribution (AA) requires capturing fine-grained stylistic characteristics, making it particularly challenging in zero-shot (ZS) settings whe

Automatic register identification for the open web using multilingual deep learning

arXiv:2406.19892v5 Announce Type: replace Abstract: This article presents multilingual deep learning models for identifying web registers -- text varieties such as news reports and discussion forums -

Autoregressive Differentiable Method for Integer Programming

arXiv:2610.02528v1 Announce Type: new Abstract: We introduce an autoregressive differentiable method to solve 0-1 integer programs. We fix an arbitrary order of the binary variables and we train a tra

Autoregressive latent diffusion for 3D molecule generation

arXiv:2607.09277v2 Announce Type: replace Abstract: Three-dimensional (3D) molecule generation has been dominated by diffusion models, which achieve strong generation quality but typically require mol

BaCP: Backbone Contrastive Pruning for Preserving Representations in Extremely Sparse Neural Networks

arXiv:2610.02524v1 Announce Type: new Abstract: Unstructured pruning at extreme sparsity often suffers from representational collapse, causing sharp drops in accuracy. To address this, we study Backbo

Balancing Multimodal Learning via Functional Progress

arXiv:2610.03035v1 Announce Type: new Abstract: Multimodal learning often suffers from modality imbalance, where the joint optimization process is dominated by a single modality. Existing methods typi

Bandits via Additive Quantized Representations

arXiv:2610.02440v1 Announce Type: new Abstract: Contextual bandits require balancing nonlinear reward modeling with online efficiency. Tree ensembles and neural methods capture nonlinearities but requ

BeeWhere: Segmenting Bumble Bee Colonies to Quantify Behavioral Effects

arXiv:2610.03051v1 Announce Type: new Abstract: Social bees are important pollinators that support biodiversity and crop pollination globally and serve as important model systems for collective behavi

Behavior Pack Optimization for Video MLLM Post-Training

arXiv:2610.03141v1 Announce Type: new Abstract: Video multimodal large language models (MLLMs) keep climbing video question answering benchmarks, yet shuffling the frames, masking the segment that sup

Beyond Random Splits: Evaluating Drug-Target Affinity Models Under Chemically and Biologically Motivated Distribution Shifts Copy

arXiv:2610.03456v1 Announce Type: new Abstract: Drug-target affinity (DTA) prediction is widely used to prioritize candidate compounds before costly experimental screening. DTA models are often compar

Model Releases

Beyond Single Videos: Benchmarking and Active Evidence Seeking for E-Commerce Cross-Video Reasoning

model-releasesarxiv-cs-ai

arXiv:2610.03099v1 Announce Type: cross Abstract: E-commerce videos are information-dense and frequently compared by consumers evaluating products and merchants assessing marketing strategies. However

Broken scale symmetries in undercomplete linear autoencoders

arXiv:2610.03640v1 Announce Type: new Abstract: Neural network loss landscapes have many symmetries, which are preserved by gradient flow but broken by finite-stepsize stochastic gradient descent (SGD

Budgeted Cache Repair for Cross-Context KV-Cache Reuse

arXiv:2610.02233v1 Announce Type: cross Abstract: Cross-context KV-cache reuse predicts a shared segment's keys and values under a new prefix instead of recomputing them, and has been reported to do s

CalCErt: Bin-wise Certification of Confidence Calibration in Medical Image Classification

arXiv:2610.03142v1 Announce Type: new Abstract: Deep neural networks remain vulnerable to adversarial perturbations, which can distort not only predictions but also confidence scores, undermining unce

Can SGD Handle Heavy-Tailed Noise?

arXiv:2508.04860v2 Announce Type: replace-cross Abstract: Stochastic Gradient Descent (SGD) is a cornerstone of large-scale optimization, yet its theoretical behavior under heavy-tailed noise -- commo

Can We Trust LLMs on Memristors? Diving into Reasoning Ability under Non-Ideality

arXiv:2603.13725v2 Announce Type: replace Abstract: Memristor-based analog compute-in-memory (CIM) architectures provide a promising substrate for the efficient deployment of Large Language Models (LL

Capability Scaling-Down Laws for LLM Compression

arXiv:2610.02462v1 Announce Type: cross Abstract: LLM compression reduces inference costs and memory requirements, but selecting a method and configuration remains largely empirical because comparable

ChromaGS: Text-Driven Semantic Editing of 4D Gaussian Avatars

arXiv:2610.03441v1 Announce Type: new Abstract: We present ChromaGS, a method for real-time, language-guided color editing of animatable 3D Gaussian head avatars. Given a trained animatable avatar, us

Closing the Train-Test Gap in World Models for Gradient-Based Planning

arXiv:2512.09929v2 Announce Type: replace Abstract: World models paired with model predictive control (MPC) can be trained offline on large-scale datasets of expert trajectories and enable generalizat

CoLMbo-SV: A Grounded Language Model for Explainable Speaker Verification

arXiv:2609.33212v2 Announce Type: replace Abstract: Speaker verification systems achieve high accuracy but provide little account of the acoustic evidence behind their judgments. Making these systems

CoMemNet: A Continual Memory Network with Drift-Aware Sampling for Traffic Prediction

arXiv:2605.05738v2 Announce Type: replace-cross Abstract: Traffic sensor networks evolve as sensors are added and traffic distributions change, whereas most forecasting models assume a fixed node set

Confidence-Gated Cloud-Edge Cascade Triage via Variational Risk Minimization for Medical Imaging

arXiv:2610.02269v1 Announce Type: cross Abstract: Emergency chest X-ray (CXR) triage has a structural modality gap: reports arrive after triage decisions, yet multimodal foundation models require imag

Consecutive Posterior Fusion for Diffusive Recovery of Unobservable Image Structures

arXiv:2610.03261v1 Announce Type: cross Abstract: Solving severely ill-posed imaging inverse problems requires recovering image structures that are unobservable or weakly constrained by the measuremen

Contextual Flow Matching: Adaptive Step Selection in Flow Models for Efficient Visual Generation

arXiv:2610.03202v1 Announce Type: cross Abstract: Flow Matching enables high-quality visual generation via continuous-time dynamics, but inference remains costly due to multiple sequential function ev

Contrastive Neural Embeddings Reveal Individual Traits Beyond Conversational Role

arXiv:2610.03410v1 Announce Type: cross Abstract: Contrastive representation learning is increasingly used to recover low-dimensional structure from neural recordings, but its output is typically vali

Controllable Accent Normalization via Discrete Diffusion

arXiv:2603.14275v3 Announce Type: replace-cross Abstract: Existing accent normalization methods do not typically offer control over accent strength, yet many applications-such as language learning and

CORE: COverage CAlibration and Evicted-Mass REdistribution for KV Cache

arXiv:2610.02235v1 Announce Type: cross Abstract: Long-context decoding is increasingly constrained by key--value (KV) cache memory and bandwidth. Existing fixed-budget compression methods typically s

Counterfactual Action Evaluation, Observation Bottlenecks, and Representation Geometry in Joint-Embedding Predictive World Models

arXiv:2610.02860v1 Announce Type: new Abstract: Low latent prediction error does not establish that a world model distinguishes the consequences of its actions. We introduce an evaluation protocol tha

Counterfactual Predictions in Scientific Emulators Without Controlled Experiments

arXiv:2610.02252v1 Announce Type: cross Abstract: Many scientific questions require reasoning about what was never observed: What if the conditions, interventions, or history had been different? Model

Coupled reaction and diffusion governing interface evolution in solid-state batteries

arXiv:2506.10944v2 Announce Type: replace-cross Abstract: Understanding and controlling the atomistic-level reactions governing the formation of the solid-electrolyte interphase (SEI) is crucial for t

CRISP: A Framework for Clause-Reconstructed Interpretable NeuroSymbolic Propositions

arXiv:2610.02431v1 Announce Type: new Abstract: Deep neural networks achieve high accuracy through layered numerical transformations, yet their decisions remain difficult to audit because decision evi

Cross-cohort TB classification using clinical data gathered in Uganda and South Africa

arXiv:2610.03256v1 Announce Type: new Abstract: We present a first evaluation of machine learning applied to patient clinical and demographic data gathered in two different countries for the purpose o

CrowdOcc: Monocular Semantic Scene Completion for Quadruped Robots in Crowded Indoor Environments

arXiv:2610.03031v1 Announce Type: new Abstract: Monocular semantic scene completion (SSC) for quadruped robots remains underexplored in real crowded indoor environments, where human-scene occlusion di

Custom Forcing: Training-Free Subject Customization for Autoregressive Video Generation

arXiv:2610.02914v1 Announce Type: new Abstract: Autoregressive video models can generate minute-long videos in real time, but they produce generic subjects from text rather than specific subjects from

DAGS: Disentangled Appearance-and-Geometry Steering of a Frozen Image DiT for Temporally Stabilized Generative Rendering

arXiv:2610.02567v1 Announce Type: cross Abstract: Diffusion transformers (DiTs) generate high-fidelity images from text and image conditions, but their outputs carry large variance and their faithfuln