Search: “pretraining”

Audio for Sports Highlight Detection: A Comparative Empirical Study

arXiv:2609.17923v1 Announce Type: new Abstract: Sports highlight detection aims to identify the most exciting and meaningful moments from long sports videos. While existing methods often emphasize vis

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

CompArt: Operationalizing Aesthetic Alignment in Text-to-Image Generation via Principles of Art

DGX agent

arXiv:2503.12018v2 Announce Type: replace-cross Abstract: Text-to-Image (T2I) diffusion models have made rapid progress on semantic alignment (generating what is described in the prompt), yet users st

safetyarxiv-cs-ai

17 Sept 2026

Copy What Is Seen, Generate What Is Not: Training-Free Anomaly-Aware Video Restoration

arXiv:2609.18836v1 Announce Type: new Abstract: A surveillance system that detects an anomaly often has to repair the footage as well, yet the two tasks are studied in isolation: training-free anomaly

CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

arXiv:2609.18462v1 Announce Type: cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts. Their reconstruction

Local Ai

Disentangling Algorithmic Bias from Archival Artifacts: A Controlled Audit of Vision-Language Model Valuation in Metropolitan Museum Archives

arXiv:2609.17572v1 Announce Type: new Abstract: Auditing vision-language models (VLMs) for societal bias requires distinguishing direct algorithmic valuation disparities from confounders embedded with

local-aiarxiv-cs-lg

Energy-Regularized Imitation Learning for Force- and Work-Aware Robotic Manipulation

arXiv:2609.18164v1 Announce Type: new Abstract: This paper studies energy-aware manipulation as a physically grounded learning problem. We define a joint-space mechanical-work proxy from joint torque

Face-voice Association across LAnguages and Gender (FLAG) 2027 Challenge Evaluation Plan

arXiv:2609.17913v1 Announce Type: new Abstract: Face--voice association models may rely on language or gender cues in the voice rather than on speaker-specific voice characteristics, which can lead to

How Many Labels Does Model Choice Need? Certificates and Budgets for Selective Prediction

arXiv:2609.18622v1 Announce Type: new Abstract: Classifiers can make identical predictions yet require labels to compare their selective performance: confidence ranks weight the same errors differentl

safetyarxiv-cs-lg

iMINDBench: iEEG Multi-Institution Neural Decoding Benchmark

arXiv:2609.18104v1 Announce Type: new Abstract: Intracranial electroencephalography (iEEG) is widely used to record electrical activity directly from electrodes inside the human brain, making it an at

Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data

arXiv:2609.18842v1 Announce Type: new Abstract: The scaling laws hold that a language model grows more capable with more parameters and more training data, and Mixture-of-Experts (MoE) architectures h

Knowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering

arXiv:2609.18317v1 Announce Type: cross Abstract: Large language models (LLMs) suffer from a long-tail deficit: culturally specific facts, particularly those concerning underrepresented regions such a

Label-free steering: Compressing test-time reinforcement learning into bias-only subspaces

arXiv:2609.18587v1 Announce Type: cross Abstract: Test-time reinforcement learning (TTRL) enables models to improve their reasoning without relying on labeled training data, but existing approaches ty

LaSeD: Label-Semantic Self-Distillation for Visual-Only Surgical Phase Recognition

arXiv:2609.18971v1 Announce Type: new Abstract: Surgical phase recognition maps each video frame to a clinically meaningful workflow phase, supporting context-aware assistance, documentation, and post

Lost in Perception: Isolating Perceptual and Reasoning Failures in Multimodal Physics and Geometry Reasoning

arXiv:2609.18991v1 Announce Type: new Abstract: Multimodal LLMs report strong performance on scientific reasoning benchmarks, yet most treat perception and reasoning as a single measurable process. We

{M}^2Tok: Multi-head Multi-codebook Discrete Action Tokenization for Vision-Language-Action Models

arXiv:2609.18259v1 Announce Type: cross Abstract: Recent advancements have successfully adapted autoregressive language models to process multimodal signals, such as images and actions. Since raw acti

safetyarxiv-cs-ai

METALICA: METAdynamics and repLICA exchange for enhanced diffusion sampling

arXiv:2609.17823v1 Announce Type: cross Abstract: Many proteins function through transitions between conformational states, yet rare states are rarely sampled by diffusion models trained on an equilib

safetyarxiv-cs-lg

MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening

arXiv:2602.23994v2 Announce Type: replace-cross Abstract: Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) precedes dementia. Structural MRI pro

NeuroECG: ECGFounder-Based Deep ECG Representation for EEG-Free Neurological Prognostication After Cardiac Arrest

arXiv:2609.18891v1 Announce Type: cross Abstract: Neurological prognostication after cardiac arrest commonly relies on electroencephalography (EEG). However, EEG demands high clinical resources. Bedsi

PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection

model-releasesarxiv-cs-cl

arXiv:2609.19143v1 Announce Type: cross Abstract: Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language model

Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization

arXiv:2603.27526v2 Announce Type: replace Abstract: Protein fitness optimization is a discrete search problem, and the representation used for prediction also determines the neighborhood graph travers

researcharxiv-cs-lg

QMSR: Query-Conditioned Mask-wise Expert Routing for Robust Open-Vocabulary Underwater Object Retrieval

arXiv:2609.18752v1 Announce Type: new Abstract: Open-vocabulary object retrieval remains challenging in complex underwater environments. Although underwater image enhancement (UIE) can improve visual

RAF-VLA: Representation Alignment with the Future for End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2609.17728v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models for autonomous driving have incorporated world modeling by predicting future driving scenes alongside driving

SEA-LION-v4.8: A Technical Report

model-releasesarxiv-cs-cl

arXiv:2609.18310v1 Announce Type: new Abstract: We introduce Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network (SEA-LION) built upon NVIDIA Nemotron 3. The family includes 3

Selective Prediction and Uncertainty-Aware Referral for Pap Smear Classification

arXiv:2609.17545v1 Announce Type: new Abstract: Deep learning models for cervical cytology are almost always evaluated as if every prediction must be acted upon, yet a screening system deployed alongs

SFT or RL for Tool-Calling Agents? A Controlled Study Across Data, Method, and Scale

model-releasesarxiv-cs-cl

arXiv:2609.17848v1 Announce Type: new Abstract: Limited controlled evidence exists on how training data, adaptation method, and model scale jointly affect tool-calling performance in language-model ag

TAO-Force: Unifying Force-Aware Perception and Fast-Slow Control for Contact-Rich Manipulation

arXiv:2609.18497v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong performance across diverse robotic manipulation tasks, yet their predominantly vision-centr

Temperon: Full-Time SAM Quality at a Third Less Wall-Clock

arXiv:2609.17575v1 Announce Type: new Abstract: Sharpness-aware minimization (SAM) doubles the cost of every training step, yet its benefit concentrates where training ends. We study where an expensiv

Local Ai

The Attention Within: Consensus Dynamics in Selective State Space Models

arXiv:2609.17997v1 Announce Type: cross Abstract: Selective state space models (SSMs) have recently emerged as a compelling alternative to transformers, combining competitive performance with substant

local-aiarxiv-cs-ai

The Unbearable Weight: Scaling Models and Methods for UAV Audio Classification

arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp

Veo-Act: Enhancing VLA Policies with Frontier Video Models

arXiv:2604.04502v2 Announce Type: replace Abstract: Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video genera

VLM-MPPI: Grounding Natural Language in Behaviorally Diverse Trajectories for Aerial Navigation

arXiv:2609.18451v1 Announce Type: new Abstract: We present a hierarchical UAV navigation framework that aligns natural-language intent with dynamically feasible flight behaviors in cluttered indoor en

Tutorials

Walking the Score Manifold: Continuous-time Generative Dynamics on Learned Data Manifolds

arXiv:2609.17901v1 Announce Type: cross Abstract: Generative modeling of time-dependent data is typically formulated on a discrete temporal grid, restricting supervision to the observed timestamps in

tutorialsarxiv-cs-ai

Bridging the Perceptual Gap: Residual-Enhanced Downscaling and Manifold-Aware Perception Alignment Adaptation for NR-IQA

arXiv:2609.16664v1 Announce Type: new Abstract: Leveraging Large Vision-Language Models like CLIP has recently set new benchmarks for No-Reference Image Quality Assessment (NR-IQA). However, the contr

Can Knowledge Transfer Parameters Be Learned? LePoKet for Efficient Robotic Vision

arXiv:2609.16637v1 Announce Type: new Abstract: Efficient perception is central to robotic systems operating under constrained computation, memory, and latency budgets. Knowledge transfer from larger

CLARE: Scalable Class-Incremental Continual Learning via a Sparsity-Based Framework

arXiv:2609.17026v1 Announce Type: cross Abstract: Continual learning must balance the learning of new knowledge with the retention of previously learned knowledge to incrementally learn tasks from a d

De-GAN - Dynamic Parameter Tuned GAN for 3D Medical Image Segmentation: A Step Towards Generalisation

arXiv:2609.16755v1 Announce Type: new Abstract: Brain tumor segmentation remains difficult because enhancing tumor (ET) has low contrast and overlaps surrounding tissue, while scanner and site variati

DecoGS: Adaptive Static-Dynamic Decoupling of 3D Gaussians for Free-Viewpoint Video Streaming

arXiv:2609.17230v1 Announce Type: new Abstract: Streaming 3D reconstruction demands both speed and temporal fidelity, goals that existing methods undermine by updating every Gaussian every frame, even

Drift Field Net: Learning Ocean Lagrangian advection fields from in-situ and satellite observations

arXiv:2609.16288v1 Announce Type: new Abstract: The North Pacific Subtropical Gyre (NPSG) is a major accumulation zone for floating plastic debris, resulting from basin-scale convergent ocean circulat

researcharxiv-cs-lg

Early-Bird Decoding: Accelerating Diffusion LLMs with Learnable Block Sizes and Parallel Sampling

arXiv:2609.16450v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising parallel decoding paradigm as an alternative to autoregressive generation through iterative

Extremely coarse learning objectives induce human-aligned representations in AI vision models

arXiv:2605.05556v2 Announce Type: replace Abstract: Artificial neural networks trained on visual tasks develop internal representations resembling those of the primate visual system, a discovery that

safetyarxiv-cs-cv

FreqSpaNet: Frequency and Spatial Learning of SFPF for Physical Layer Hardware Integrity Detection

arXiv:2609.17491v1 Announce Type: new Abstract: Unauthorized hardware replacement can preserve a wireless device's logical identity while altering its physical implementation, posing a challenge to ha

researcharxiv-cs-lg

GeoCrossBench: Cross-Band Generalization for Remote Sensing

arXiv:2511.02831v2 Announce Type: replace Abstract: The data for remote sensing is constantly acquired, and new data comes from a growing number and diversity of satellites, while the vast majority of

GeoLAM: Learning Geometry-Grounded Latent Actions from Unlabeled Human Videos

arXiv:2609.17099v1 Announce Type: new Abstract: Human videos provide rich manipulation experience, but extracting action representations that preserve useful motion remains challenging. Visual reconst

How Good Are Time-Series Foundation Models for Pedestrian Crowd Count Forecasting? A Cross-Dataset Comparative Study

arXiv:2609.16415v1 Announce Type: cross Abstract: Pedestrian-count forecasting supports pedestrian-oriented Intelligent Transportation Systems (ITS), including crowd monitoring, pedestrian-traffic sta

MedPCFM-TED: One-Step Point Cloud Flow Matching for Implant Generation via Teacher-Guided Endpoint Distillation

arXiv:2609.16934v1 Announce Type: new Abstract: Cranial implant generation is an important task in medical imaging. Recent point cloud based generative methods, particularly flow matching, offer stron

NeuroTS-Net: Multi-Class Semantic Segmentation of Pediatric Brain Tumors in Multi-Modal MRI

arXiv:2609.16873v1 Announce Type: new Abstract: Pediatric brain tumors are a leading cause of cancer-related mortality in children, and their small, rare, and often low-contrast subregions make accura

Nonsmooth Optimization via Orthogonalized Momentum

arXiv:2609.13677v1 Announce Type: cross Abstract: Modern real application problems involve matrix-valued parameters, yet conventional optimizers treat them as vectors, thereby motivating matrix-aware

OPEN-1B: A Fully Auditable Training Run

arXiv:2609.17380v1 Announce Type: new Abstract: Open-source language models have a reproducibility problem. Despite releasing weights, training data, and recipes, none of them are provably reproducibl