Search: “pretraining”

Fast and Accurate: An Adaptive VLA Inference Framework through Environment-aware Model Selection

model-releasesarxiv-cs-lg

arXiv:2608.06434v1 Announce Type: cross Abstract: Embodied intelligence demands both long-horizon reasoning and real-time closed-loop responsiveness. Recent dual-system Vision-Language-Action (VLA) ar

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Local Ai

HazeSpikeMamba: Coupling Spiking-Inspired and State-Space Features for Self-Supervised Real-World Dehazing

DGX agent

arXiv:2608.06886v1 Announce Type: new Abstract: Dehazing networks are commonly trained on synthetic hazy-clear pairs, but their performance often drops on real photographs. Synthetic haze generated us

local-aiarxiv-cs-cv

10 Aug 2026

Latent Fact-Checking: Detecting Misinformation through Activation Engineering

model-releasesarxiv-cs-cl

arXiv:2608.06417v1 Announce Type: cross Abstract: The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level ling

LSEAD: A Privacy-Preserving LLM-Based Speech Analysis Framework for Early Alzheimer's Disease Screening

arXiv:2608.07378v1 Announce Type: cross Abstract: Early diagnosis of Alzheimer's disease (AD) is critical for enabling timely interventions that may slow disease progression and improve patient outcom

Optimizing Spectral Prediction in MXene-Based Metasurfaces Through Multi-Channel Spectral Refinement and Savitzky-Golay Smoothing

arXiv:2602.08406v2 Announce Type: replace-cross Abstract: The prediction of electromagnetic spectra for MXene-based solar absorbers, where MXenes are a family of two-dimensional transition metal carbi

researcharxiv-cs-ai

Policy-Masked Private Experts: Auditable and Reversible Capability Access Control in Sparse MoE Models

arXiv:2608.06690v1 Announce Type: cross Abstract: Most language-model access controls regulate behavior while leaving the same computation available to every request. We study a different systems ques

Representation-driven Endoscopic Visual Embedding Alignment for Latent Generation

arXiv:2608.07176v1 Announce Type: cross Abstract: Developing foundation generative models for endoscopy is limited by the gap between natural and clinical images and the computational cost of training

safetyarxiv-cs-ai

Agents

SimWAM: A Simple World Action Model for End-to-End Autonomous Driving

arXiv:2608.07468v1 Announce Type: new Abstract: World-Action Models (WAMs) improve end-to-end autonomous driving by transferring video dynamics priors to action prediction, but existing methods requir

agentsarxiv-cs-cv

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge

arXiv:2608.07106v1 Announce Type: new Abstract: Deploying three-dimensional deep learning frameworks to low-power embedded processors is bottlenecked by the unstructured nature of spatial data and the

applicationsarxiv-cs-lg

Test-Time Adaptation with Online Personalized Energy-Based Cache for Fine-Grained Video Expression Recognition

arXiv:2608.06467v1 Announce Type: new Abstract: Facial expression recognition (FER) in videos is challenging because models must identify subtle, temporally evolving affective states that vary across

UAV3DCrop: Benchmarking 3D Reconstruction in Repeated Multi-Angle UAV Crop Surveys

arXiv:2608.06404v1 Announce Type: new Abstract: Accurate 3D crop monitoring underpins data-driven precision agriculture by enabling field-scale analysis of plant structure, growth dynamics, and manage

Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection

arXiv:2608.07015v1 Announce Type: new Abstract: Omni-domain infrared small target (IRST) detection is crucial for infrared surveillance, yet remains challenging due to heterogeneous imaging domains an

A Study of ASR Adaptation and Representation Dimensionality Reduction in Persian Speech Emotion Recognition Using Whisper

arXiv:2608.05165v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) in low-resource languages remains a challenging problem due to limited labeled data. In this work, we study the use o

researcharxiv-cs-ai

Audio-to-Score Transcription using Pre-trained Features, Data Augmentation, and the New SheetSage-A2S Dataset

arXiv:2608.06165v1 Announce Type: cross Abstract: Existing audio-to-score (A2S) systems primarily focus on classical music, and the application to popular music remains underexplored. This paper first

Beyond Full-Model Rollback: AuroSFT for Adapter-State Multi-Task Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2608.05250v1 Announce Type: new Abstract: Multi-task supervised fine-tuning (SFT) often casts a heterogeneous data mixture as a single optimization problem, even though different tasks may reach

Beyond Sequence Order: Syntax-Informed Positional Embeddings for Transformers

arXiv:2608.06111v1 Announce Type: cross Abstract: Positional embeddings (PE) in Transformers encode token distance and order but are largely agnostic to extit{syntactic structure}. We introduce extbf{

Big, Bright, or Invisible: A Frozen-Feature Benchmark of 3D CT Foundation Models

arXiv:2608.05960v1 Announce Type: cross Abstract: Routine CT interpretation is inherently comprehensive, capturing incidental findings across the entire scan volume. 3D CT foundation models could assi

Cautious Context Steering for Language Model Personalization

arXiv:2608.05813v1 Announce Type: new Abstract: Personalizing language models (LMs) to individual user preferences is essential for aligning responses with diverse goals and backgrounds. Existing meth

tutorialsarxiv-cs-ai

DARAD: Dual Adapters and Ranking-Aware Distillation for Continual Remote Sensing Image-Text Retrieval

arXiv:2608.06059v1 Announce Type: new Abstract: With the rapid growth of Earth observation technologies, remote sensing archives are rapidly expanding, making remote sensing image-text retrieval (RS-I

safetyarxiv-cs-cv

Discrete energy as an exact label-free training objective for finite-element surrogates

arXiv:2608.05437v1 Announce Type: cross Abstract: Supervised training of finite-element (FE) surrogate models requires reference solutions, and each reference solution is obtained by solving the syste

researcharxiv-cs-lg

Dynamic Object Masks as Goal Representations for Visual Goal-Conditioned Reinforcement Learning

arXiv:2510.06277v2 Announce Type: replace Abstract: Goal-conditioned reinforcement learning (GCRL) offers a unified way to pursue diverse tasks, yet most existing methods rely on state- or position-ba

applicationsarxiv-cs-cv

GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions

arXiv:2608.06332v1 Announce Type: new Abstract: Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning a

safetyarxiv-cs-ro

HERA: Historical Evidence Routing Adapter for Physical Prediction in Latent World Models

arXiv:2608.05523v1 Announce Type: new Abstract: Predictive video models have emerged as promising world models by learning latent visual dynamics from large-scale video. Yet these models remain challe

Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising

arXiv:2510.05589v3 Announce Type: replace-cross Abstract: Effective time series forecasting enables various real-world applications, benefiting from the proliferation of mobile devices. However, the v

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment

model-releasesarxiv-cs-ro

arXiv:2608.05674v1 Announce Type: new Abstract: Robot data is scarce, so generalist policies need to learn from heterogeneous sources, including human egocentric video, simulation, and real robots, wh

Just saw that the LLMs-from-scratch repository passed 100,000 stars on GitHub! This is super cool and motivating. I am really happy to see t…

model-releasessebastian-raschka--x

Just saw that the LLMs-from-scratch repository passed 100,000 stars on GitHub! This is super cool and motivating. I am really happy to see that this open-source repo has helped so many people. Thanks

MetaboLLM: a metabolomics-specialized large language model for biochemical knowledge integration and predictive metabolite graph construction

model-releasesarxiv-cs-lg

arXiv:2608.06253v1 Announce Type: new Abstract: Metabolomics knowledge is distributed across heterogeneous resources and remains difficult to translate into predictive representations. We developed Me

MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation

arXiv:2603.25406v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models map visual observations and natural-language instructions to robot actions; however, hierarchical and autoregres

applicationsarxiv-cs-ro

Patient Pose Assessment Using a CT-Based Framework for Synthetic Data Generation

arXiv:2608.06126v1 Announce Type: new Abstract: An adequate diagnostic quality of radiographs is essential for reliable diagnoses and treatment planning. The patient's pose during radiography is one o

Reinforcing Action Policies by Prophesying

arXiv:2511.20633v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) policies excel in aligning language, perception, and robot control. However, most VLAs are trained purely by imitation,

tutorialsarxiv-cs-ro

RxnCLF: Contrastive Transformation-Aware Reaction Foundation Model for Improved Reactivity Prediction

arXiv:2608.06259v1 Announce Type: new Abstract: Reaction yield prediction remains challenging because labeled data are scarce and reaction space is both combinatorially large and sparsely populated, l

tutorialsarxiv-cs-lg

Spectral Aliasing Pretext: A novel task for Self-Supervised fault diagnosis in rotating machinery

arXiv:2608.05705v1 Announce Type: cross Abstract: Deep learning is a new way for machinery fault diagnosis but requires extensive labeled data, a scarce resource in industrial settings. We propose Spe

tutorialsarxiv-cs-ai

Text-Guided Refinement of Multi-sequence Glioma Subregion Segmentation with a Vision-Language Foundation Model

arXiv:2608.05389v1 Announce Type: new Abstract: Background: Accurate glioma subregion delineation is important for radiotherapy planning and longitudinal monitoring, but manual contour correction is t

Wan-Animate-2: Pushing the Application Boundaries of Character Animation

arXiv:2608.06009v1 Announce Type: new Abstract: Character image animation remains a foundational yet challenging task in computer vision. Existing approaches can be broadly categorized into three para

Why the Third Axis Is Freedom

arXiv:2608.05423v1 Announce Type: cross Abstract: In generative training, a model produces an output and is penalised for its difference from an example. With one output per comparison, a model that p

researcharxiv-cs-ai

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series

arXiv:2608.04706v1 Announce Type: new Abstract: Monitoring of offshore wind energy infrastructure life cycles, especially during the deployment phase, is an important contribution for stakeholders to

applicationsarxiv-cs-lg

Contrastive Diffusion Alignment: Learning Structured Latents for Controllable Generation

arXiv:2510.14190v3 Announce Type: replace Abstract: Diffusion models excel at generation, but their latent spaces are high dimensional and not explicitly organized for interpretation or control. We in

safetyarxiv-cs-lg

COSMO: Consensus-Driven Shift Modulation for Source-Free Domain Adaptation

arXiv:2608.04604v1 Announce Type: new Abstract: Source-free domain adaptation (SFDA) adapts a source-trained model to an unlabeled target domain without source data, a practical setting under privacy

safetyarxiv-cs-cv

Local Ai

From Understanding to Erasing: Towards Complete and Stable Video Object Removal

arXiv:2604.01693v2 Announce Type: replace Abstract: Video object removal aims to erase target objects while reconstructing visually plausible and temporally coherent content. However, target objects o

local-aiarxiv-cs-cv

GUARD: Grounding Uncertainty and Ablation-Based Risk Detection for Diffusion-Based VLAs

arXiv:2608.04510v1 Announce Type: cross Abstract: Diffusion-based vision-language-action (VLA) policies can generate plausible actions even when their predictions are weakly grounded in the visual and

Kathleen Writes: Autoregressive Generation and Data Scaling Without Attention

model-releasesarxiv-cs-cl

arXiv:2608.04678v1 Announce Type: new Abstract: Papers 1-2 of the Kathleen series showed that a byte-level, attention-free architecture built from a wavetable encoder and multi-scale reverberant state

Label-Free Target-Domain Adaptation for Unconstrained Event-Image Feature Matching via Dual-Stage Distillation

arXiv:2607.10082v2 Announce Type: replace Abstract: Building pixel-level correspondence between event and image data is a fundamental task for multi-sensor systems. However, existing cross-modal match

Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications

arXiv:2509.08604v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-traini

safetyarxiv-cs-ai

MESH: Memory-Efficient Sinkhorn Optimization for Mixture-of-Experts Training

arXiv:2608.04407v1 Announce Type: cross Abstract: Memory-efficient matrix optimizers such as Sinkhorn gradient descent remove most AdamW optimizer state for dense Transformer matrices, but direct appl

MobileWAM: Bridging World Action Models to Mobile Manipulation with Chain-of-Foresight

arXiv:2608.04657v1 Announce Type: new Abstract: World action models (WAMs) built on video generation backbones are a rising recipe for robot learning, yet remain confined to tabletop manipulation. Mob

RiboSphere: Learning Unified and Efficient Representations of RNA Structures

arXiv:2603.19636v2 Announce Type: replace Abstract: Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimen

researcharxiv-cs-lg

Strengthening Target-Language Features: SAE-Based Steering for Multilingual Inference

model-releasesarxiv-cs-cl

arXiv:2608.04904v1 Announce Type: new Abstract: Multilingual large language models exhibit substantial performance differences across languages, while existing adaptation methods often require paramet

Towards Trustworthy Hypergraph Neural Networks under Label Noise

arXiv:2608.04377v1 Announce Type: cross Abstract: Hypergraph neural networks (HGNNs) have demonstrated remarkable capabilities in processing complex higher-order relationships. However, their performa