Search: “pretraining”

Which Question Is Your Attention Metric Answering? Attention Rows as Compositional Data

arXiv:2608.14712v1 Announce Type: cross Abstract: Each row of a transformer's attention matrix is a probability distribution over tokens, and in trained models most of that probability lands on a sing

researcharxiv-cs-ai

18 Aug 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Wolff-Parkinson-White Detection at 471:1 Class Imbalance: A Leakage-Controlled Study of the Data Bottleneck

DGX agent

arXiv:2608.14633v1 Announce Type: cross Abstract: Wolff-Parkinson-White (WPW) syndrome is a congenital cardiac pre-excitation, clinically important and often missed on the resting 12-lead ECG. Detecti

researcharxiv-cs-lg

18 Aug 2026

Agents

World-in-World: World Models in a Closed-Loop World

arXiv:2510.18135v2 Announce Type: replace Abstract: Generative world models (WMs) can now simulate worlds with striking visual realism, which naturally raises the question of whether they can endow em

agentsarxiv-cs-cv

18 Aug 2026

A Calibrated Test of Internal Action Maps: State Signals Without Global Affine Closure

arXiv:2608.13626v1 Announce Type: new Abstract: A hidden state signal can be decodable or causally usable without supporting a reusable action map. We test whether action maps fitted without a source

AI Research Preference Models

arXiv:2608.13940v1 Announce Type: new Abstract: AI research agents (AIRA) can now propose, implement, and evaluate their own machine learning experiments, but progress on frontier tasks is throttled b

Bridging Network Fragmentation: A Semantic-Augmented DRL Framework for UAV-aided VANETs

arXiv:2603.18871v2 Announce Type: replace Abstract: Urban Vehicular Ad-Hoc Networks (VANETs) can become fragmented because buildings obstruct wireless links and vehicle mobility continuously changes t

CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets

arXiv:2608.14403v1 Announce Type: new Abstract: Subject-driven image personalization---generating new images that preserve the identity of one or several reference subjects in novel scenes---is a foun

GALA: Generation-Aware Cross-Modal Alignment for Text-to-Time-Series Synthesis

arXiv:2608.13741v1 Announce Type: new Abstract: Synthesizing time series from natural language is emerging as the most expressive form of controllable time series generation. However, existing text-co

GhostPoint: Self-Supervised Representation Learning by Hallucinating Occluded LiDAR Structure

arXiv:2608.14428v1 Announce Type: new Abstract: 3D object detection from LiDAR point clouds is a core problem in autonomous driving. Recent advances in self-supervised learning (SSL) enable scalable p

local-aiarxiv-cs-cv

GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings

arXiv:2608.13698v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), often optimized with Group Relative Policy Optimization (GRPO), has become a central recipe for i

Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning

arXiv:2608.14290v1 Announce Type: new Abstract: We introduce Mobius-v0, an architecture that comprises a globally shared Memory (FFN) that stores knowledge vectors and multiple Reasoners (Self-Attn) t

researcharxiv-cs-ai

Hardware

LatentAM: Real-Time, Large-Scale Latent Gaussian Attention Mapping via Online Dictionary Learning

arXiv:2602.12314v2 Announce Type: replace-cross Abstract: We present LatentAM, an online 3D Gaussian Splatting (3DGS) mapping framework that builds scalable latent feature maps from streaming RGB-D ob

hardwarearxiv-cs-cv

Learning Perceptual Representations for Gaming NR-VQA with Multi-Task FR Signals

arXiv:2602.11903v3 Announce Type: replace-cross Abstract: No-reference video quality assessment (NR-VQA) for gaming videos is challenging due to limited human-rated datasets and unique content charact

tutorialsarxiv-cs-cv

MINT: A Universal Zero-Shot Predictor for Transaction Data

arXiv:2608.14198v1 Announce Type: cross Abstract: Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalizatio

Point-Supervised Skeleton-Based Human Action Segmentation

arXiv:2603.06201v2 Announce Type: replace Abstract: Skeleton-based temporal action segmentation is a fundamental yet challenging task, playing a crucial role in enabling intelligent systems to perceiv

tutorialsarxiv-cs-cv

RefGC-SR^2: Reference-guided Super-Resolution and Refinement of AI Generated Content

arXiv:2606.15158v2 Announce Type: replace Abstract: Reference-guided generation (e.g., object compositing, customization) has progressed rapidly, yet current pipelines share a fundamental limitation:

applicationsarxiv-cs-cv

Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation

arXiv:2608.14379v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently achieved promising performance in robotic manipulation. However, existing benchmarks mainly evaluate

Shift Aware Transfer Learning with Adaptive Dual-Encoder Fusion for PM Forecasting in Data-Limited Environments

arXiv:2608.14456v1 Announce Type: new Abstract: Short-horizon forecasting of fine particulate matter (PM2.5) remains difficult when observations from the target domain are limited and the statistical

local-aiarxiv-cs-ai

StreamHear: Domain-Adapted Pseudo-Labeling for Semi-Supervised Streaming Speech Recognition

arXiv:2608.13717v1 Announce Type: new Abstract: Streaming automatic speech recognition (ASR) underperforms on domain-shifted target audio, where labeled in-domain data is costly to prepare while unlab

researcharxiv-cs-cl

BavGround: A Benchmark for Regional Cultural Grounding and Dialect Competence in Bavarian

model-releasesarxiv-cs-cl

arXiv:2608.12894v1 Announce Type: new Abstract: Cultural evaluation of large language models (LLMs) often focuses on high-resource standard languages, leaving regional culture and dialect communities

Can Generalist Vision Language Models (VLMs) Rival Specialist Medical VLMs? Benchmarking and Strategic Insights

arXiv:2506.17337v5 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have shown promise in automating image diagnosis and interpretation in clinical settings. However, developing sp

researcharxiv-cs-ai

CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation

arXiv:2608.12944v1 Announce Type: new Abstract: Electrocardiography (ECG), photoplethysmography (PPG), and phonocardiography (PCG) provide complementary views of the same cardiac cycle, yet existing c

tutorialsarxiv-cs-lg

DARTree: Speculative Diffusion Decoding with Autoregressive Draft Trees

arXiv:2608.13524v1 Announce Type: new Abstract: Speculative decoding losslessly accelerates autoregressive language models by verifying multiple draft tokens in parallel. Diffusion-based drafters furt

Decoding Task Progress from VLA Representations

arXiv:2608.13474v1 Announce Type: new Abstract: Vision-language-action models (VLAs) are moving rapidly towards deployment as general-purpose manipulation policies, but we currently lack basic tools f

safetyarxiv-cs-ro

Fidelity-Constrained Anchoring for Black-Box Denoisers

arXiv:2608.13194v1 Announce Type: new Abstract: We propose a fidelity-constrained framework that anchors the output of a black-box denoiser to its input without retraining and with little additional c

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization

arXiv:2608.12687v1 Announce Type: new Abstract: Bayesian optimization (BO) is a sample-efficient framework for analog circuit topology search, where evaluating each candidate topology can require cost

Agents

Geometry-Grounded Unified 3D Perception for Autonomous Driving

arXiv:2608.13147v1 Announce Type: new Abstract: Camera-based autonomous driving perception requires a shared representation that preserves metric 3D structure across synchronized multi-camera streams.

agentsarxiv-cs-cv

HounsWorld: A Multimodal World Model for Hidden Patient-State Readout, Reconstruction, and Simulation

model-releasesarxiv-cs-cv

arXiv:2608.12904v1 Announce Type: new Abstract: Clinical intelligence requires estimating a patient's underlying condition from incomplete observations rather than learning isolated mappings from scan

Intern-S2-Preview: Scientific Agentic Foundation Model

arXiv:2608.13505v1 Announce Type: cross Abstract: Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific t

LittleLearner: Language Models Under Pedagogically Controlled Knowledge Exposure

arXiv:2608.13545v1 Announce Type: cross Abstract: Modern language models are trained on heterogeneous web-scale text corpora. Consequently, studying knowledge and skill acquisition is difficult, as pr

MARCH: Scaling Recurrent Memory with Content-Routed State Anchors

arXiv:2608.12435v1 Announce Type: new Abstract: Transformers owe much of their strong long-context retrieval capability to a token-level memory that grows with context length. This flexibility, howeve

Motor, Cognitive, or Corpus? What Survives Cross-Lingual Transfer in Speech-Based Parkinsons Disease Detection

arXiv:2608.13425v1 Announce Type: new Abstract: Self-supervised learning (SSL) speech representations achieve strong performance for Parkinson's disease (PD) detection within individual corpora. Howev

researcharxiv-cs-cl

RadarGen: Automotive Radar Point Cloud Generation from Cameras

arXiv:2512.17897v2 Announce Type: replace-cross Abstract: We present RadarGen, a diffusion model for synthesizing realistic automotive radar point clouds from multi-view camera imagery. RadarGen adapt

tutorialsarxiv-cs-ai

RealMat: Realistic Materials with Diffusion and Reinforcement Learning

arXiv:2509.01134v2 Announce Type: replace-cross Abstract: Generative models for high-quality materials are particularly desirable to make 3D content authoring more accessible. However, the majority of

applicationsarxiv-cs-cv

Sampling Luck Masquerades as Allocation Gain: Auditing Test-Time Budget Allocation for Neural Combinatorial Optimization

arXiv:2608.13087v1 Announce Type: cross Abstract: Neural combinatorial optimization (NCO) solvers report the best of many sampled solutions per instance, and the sample count is, by convention, identi

Semantic Radiance Fields as Simulators for Spatial Reasoning in Real-World Scenes

arXiv:2608.13095v1 Announce Type: cross Abstract: Training and evaluating spatial reasoning in embodied agents requires diverse environments that are both geometrically faithful and semantically query

applicationsarxiv-cs-cv

Simulation-to-real transfer learning for infrared spectroscopic chemical sensing and analysis from molecules to complex samples

arXiv:2608.13341v1 Announce Type: cross Abstract: Infrared (IR) spectroscopy is widely used for chemical sensing, but extracting reliable chemical information from spectra remains challenging. Convent

SLAyiNG: A Diverse and Community-validated Dataset of Queer Slang

arXiv:2509.17449v2 Announce Type: replace Abstract: Queer vernacular is rarely studied in NLP, despite advancements in resources and evaluation for other sociolects and informal language. Because of t

StateBridge: Training-free Hidden-state Alignment for Latent Communication in LLM Multi-Agent Systems

arXiv:2608.13317v1 Announce Type: new Abstract: Large language model based multi-agent systems usually communicate in text, i.e., using discrete tokens. However, text introduces a discrete bottleneck.

Structure-preserving uncertainty quantification for GENERIC dynamics

arXiv:2608.12624v1 Announce Type: new Abstract: Structure-preserving machine learning embeds physical structure directly into model architectures, yet uncertainty quantification (UQ) for such hard-con

The Impact of Temporal Context Length and Encoding Strategies on Self-Supervised ECG Representation Learning

arXiv:2608.12695v1 Announce Type: new Abstract: Self-supervised electrocardiogram (ECG) models are often trained on a few seconds of ECG signal and, increasingly, on discretized token sequences. It re

applicationsarxiv-cs-lg

Unsupervised training of keypoint-agnostic descriptors for flexible retinal image registration

arXiv:2505.02787v3 Announce Type: replace Abstract: Current color fundus image registration approaches are limited, among other things, by the lack of labeled data, which is even more significant in t

V-RAE: Rethinking Video Latent Spaces for Generation

arXiv:2608.13556v1 Announce Type: new Abstract: Latent video generation relies on autoencoders to define a compact space in which generative models operate. Although video autoencoder architectures ha

A Neighborhood Attention Transformer Network for Enhanced 3D Segmentation of the Left Anterior Descending Artery

arXiv:2608.12274v1 Announce Type: cross Abstract: Background: Accurate segmentation of the Left Anterior Descending (LAD) artery in 3D free-breathing, non-contrast CT is critical for cardiac dose spar

COLORA: Efficient Fine-Tuning for Convolutional Models with a Study Case on Optical Coherence Tomography Image Classification

arXiv:2505.18315v3 Announce Type: replace-cross Abstract: We introduce extbf{CoLoRA} (Convolutional Low-Rank Adaptation), a parameter-efficient fine-tuning method for convolutional neural networks (CN

Consolidator: Learning Persistent Routed Memory Across Context Boundaries

arXiv:2608.11701v1 Announce Type: cross Abstract: Copying short-term memory (STM) into a slower store can preserve state across a context boundary, but persistence alone does not ensure that the retai

local-aiarxiv-cs-ai

Curvature-Aware Zeroth-Order Optimization for Memory-Efficient Test-Time Adaptation

arXiv:2608.12279v1 Announce Type: new Abstract: Test-time adaptation (TTA) aims to enhance the cross-domain performance of pre-trained models by adapting to unlabeled test data. While most existing TT

local-aiarxiv-cs-cv

Distillation of Foundation Models for Time-dependent PDEs

arXiv:2608.11937v1 Announce Type: new Abstract: Foundation models for time-dependent partial differential equations (PDEs) are trained on large and diverse collections of physical systems and can gene

local-aiarxiv-cs-lg