Search: “pretraining”

Gradual Capacity Growth for Sparse Network Discovery

arXiv:2509.25665v2 Announce Type: replace Abstract: Sparse neural network methods typically assume that the target sparsity (or density) is fixed in advance, even though the relationship between netwo

Agents

LLM-Guided Test-Time Discovery of Quantum-Chemical Approximation Algorithms

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2606.20729v1 Announce Type: cross Abstract: Quantum chemistry simulations underpin modern materials discovery, yet their impact is limited by steep computational cost and dependence on fixed app

agentsarxiv-cs-lg

23 Jun 2026

Hardware

Multi-cancer detection using a computationally efficient CNN with transfer learning

arXiv:2606.22400v1 Announce Type: new Abstract: This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer detec

hardwarearxiv-cs-cv

NeuroShield: A Device-Agnostic Foundation Model for EEG Authentication

arXiv:2606.20673v1 Announce Type: cross Abstract: A central challenge in EEG authentication is that models are typically tied to the acquisition settings in which they are trained. In particular, vari

Tutorials

On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies

arXiv:2606.17276v3 Announce Type: replace-cross Abstract: Generative recommendation (GR) has emerged as a promising direction for recommender systems. Recently, large language models (LLMs) have been

tutorialsarxiv-cs-lg

Robust Representation Learning in Masked Autoencoders

arXiv:2602.03531v2 Announce Type: replace-cross Abstract: Masked Autoencoders (MAEs) achieve impressive performance in image classification tasks, yet the internal representations they learn remain le

safetyarxiv-cs-cv

RocketPFN: Accurate Time Series Classification via In-Context Learning

arXiv:2606.21786v1 Announce Type: new Abstract: We introduce RocketPFN, a training-free pipeline for time series classification that combines random convolutional feature extraction (Rocket) with in-c

Small LLMs: Pruning vs. Training from Scratch

model-releasesarxiv-cs-lg

arXiv:2606.14150v2 Announce Type: replace Abstract: Pruning promises a shortcut to strong small language models. In this work, we examine this promise by pruning Llama-3.1-8B at pruning ratios of 0.5-

Hardware

SPOTR: Spatio-temporal Pooling One-Token Reconstruction for Universal Physiological Signal Self-supervised Learning

arXiv:2606.21973v1 Announce Type: new Abstract: Physiological signals such as EEG, ECG, and PPG are widely used in clinical monitoring. Recent self-supervised learning (SSL) methods offer an attractiv

hardwarearxiv-cs-lg

Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G

arXiv:2606.20670v1 Announce Type: new Abstract: Wireless foundation models offer a path toward reusable channel state information (CSI) intelligence for sixth-generation (6G) systems. However, existin

Wh0: Generative World Models as Scalable Sources of Egocentric Human Hand Manipulation Data

arXiv:2606.22136v1 Announce Type: new Abstract: Scaling dexterous manipulation requires generalization across objects, scenes, and tasks, yet existing data sources face a trade-off between scale and s

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning

arXiv:2606.11634v1 Announce Type: new Abstract: The rapid progress of reasoning and agentic large language models (LLMs) has increased the demand for long-context inference, but self-attention (SA) sc

BioMamba: Domain-Adaptive Biomedical Language Models

arXiv:2408.02600v3 Announce Type: replace Abstract: Background. Biomedical language models should improve performance on biomedical text while retaining general-language-modeling fluency. For Mamba-ba

Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning

arXiv:2606.11767v1 Announce Type: cross Abstract: Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains c

Local Ai

Frozen Foundation-Model Embeddings Discard Small-Lesion Signal in Chest Radiography: Implications for Pre-Deployment Evaluation

arXiv:2606.11606v1 Announce Type: new Abstract: Frozen vision-transformer (ViT) foundation-model embeddings increasingly serve as the substrate for downstream chest-radiography (CXR) pipelines, yet wh

local-aiarxiv-cs-cv

LifeSentence: Language models can encode human life course trajectories from longitudinal panel data

arXiv:2606.11220v1 Announce Type: new Abstract: Forecasting human life outcomes is important to gain insights into how individuals attain long and healthy lives. Conventional statistical approaches yi

Noise-Guided Transport for Imitation Learning

arXiv:2509.26294v2 Announce Type: replace-cross Abstract: We consider imitation learning in the low-data regime, where only a limited number of expert demonstrations are available. In this setting, me

Tabular Foundation Models for Clinical Survival Analysis via Survival-Aware Adaptation

arXiv:2606.12006v1 Announce Type: cross Abstract: Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis. W

TacCoRL: Integrating Tactile Feedback into VLA via Simulation

arXiv:2606.11743v1 Announce Type: cross Abstract: Vision-language-action (VLA) models provide strong visual, language, and action priors for robot manipulation, but visual observations alone often mis

safetyarxiv-cs-lg

AuRA: Internalizing Audio Understanding into LLMs as LoRA

arXiv:2606.11033v1 Announce Type: cross Abstract: Recent efforts to extend large language models (LLMs) to speech inputs typically rely on cascaded ASR-LLM pipelines, end-to-end speech-language models

CoCoSI: Collaborative Cognitive Map Construction for Spatial Intelligence

model-releasesarxiv-cs-cv

arXiv:2606.10401v1 Announce Type: new Abstract: Spatial intelligence is a key frontier for multimodal large language models (MLLMs), enabling them to reason about the physical world from visual experi

Domain Adapted Large Language Models for Additive Manufacturing

model-releasesarxiv-cs-lg

arXiv:2603.22017v2 Announce Type: replace Abstract: This work presents a collection of multi-modal domain adapted large language models built upon the instruction tuned variants of open weight models

Making Time Editable in Video Diffusion Transformers

arXiv:2606.10183v1 Announce Type: cross Abstract: Modern Diffusion Transformers for video generation provide limited control over the progression of time and the editing of temporal dynamics. We propo

Sigma-Branch: Hierarchical Single-Path Network Reconstruction for Dynamic Inference with Reduced Active Parameters

arXiv:2606.09924v1 Announce Type: cross Abstract: Deploying deep neural networks on memory-constrained edge accelerators is bottlenecked by per-inference off-chip weight transfer rather than computati

BareWave: Waveform-Native Flow-Matching Text-to-Speech

arXiv:2606.09048v1 Announce Type: cross Abstract: Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling. In text-to-spee

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning

arXiv:2606.09393v1 Announce Type: new Abstract: Image and video captioning are fundamental tasks that bridge the visual and linguistic domains, playing a critical role in pre-training Large Vision-Lan

Causal Longitudinal Prior-Fitted Networks for Counterfactual Outcome Prediction

model-releasesarxiv-cs-lg

arXiv:2606.05797v2 Announce Type: replace Abstract: Longitudinal treatment decisions from multivariate time-series data require predicting potential outcomes under future treatment sequences in the pr

GEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation

arXiv:2606.08530v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background s

HiMat: DiT-based Ultra-High Resolution SVBRDF Generation

arXiv:2508.07011v5 Announce Type: replace Abstract: Creating ultra-high-resolution spatially varying bidirectional reflectance functions (SVBRDFs) is critical for photorealistic 3D content creation, t

safetyarxiv-cs-cv

How Much MRI Preprocessing Is Enough? A Cost-Utility Study for Brain MRI Foundation Models

arXiv:2606.08164v1 Announce Type: new Abstract: MRI preprocessing defines the input distribution seen by brain MRI foundation models, yet it is usually treated as routine data cleaning rather than a m

Two Bridges, One Pathway: From VLMs to Generalizable VLAs with Embodied Trajectory-Coupled Data

arXiv:2606.08520v1 Announce Type: new Abstract: Vision-language models (VLMs) are powerful general-purpose reasoners, yet converting them into robot control policies (VLAs) is surprisingly difficult.

Uncertainty-Aware Intention Prediction for Human-to-Robot Assembly Teleoperation

arXiv:2606.08341v1 Announce Type: new Abstract: In assisted teleoperation for human-robot collaboration, accurate intention prediction is critical for enabling timely and reliable robotic assistance d

researcharxiv-cs-ro

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs

arXiv:2606.06574v1 Announce Type: new Abstract: Large language models (LLMs) perform inference by following a fixed depth and order, non-recurrent execution of all layers. We reveal the wide existence

STREAM: Stochastic Riemannian Flow Matching with Anisotropic Decoder for Digital Histopathology Image Generation

arXiv:2606.07036v1 Announce Type: cross Abstract: Synthetic histopathology image generation addresses critical challenges in computational pathology, including patient privacy and the growing need for

TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics

arXiv:2602.15084v2 Announce Type: replace-cross Abstract: We present TokaMind, to our knowledge the first open-source foundation model for tokamak plasma dynamics, based on a Multi-Modal Transformer (

Video-Based Prediction of In-Flight Particle Characteristics in Atmospheric Plasma Spraying

arXiv:2606.07416v1 Announce Type: new Abstract: Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quali

Boosting Brain-to-Image Decoding with TRIBE v2 Data Augmentation

arXiv:2606.06345v1 Announce Type: new Abstract: Brain decoding is limited by the availability of labeled neural data, and remains challenging in low-data regimes. To address this issue, we investigate

6 Jun 2026

DRIFT: A Residual Flow Adapter for Decoding Continuous Outputs in Vision-Language Models

arXiv:2606.05758v1 Announce Type: new Abstract: Many modern vision-language models (VLMs) build on autoregressive decoding of discrete tokens. While text-based output interfaces enable scalable pretra

Harnessing Structural Context for Entity Alignment Foundation Models

arXiv:2606.06109v1 Announce Type: new Abstract: Entity alignment (EA) aims to identify equivalent entities across heterogeneous knowledge graphs (KGs) and is a key component of knowledge fusion and cr

Applications

In-Context Multiple Instance Learning

arXiv:2606.06458v1 Announce Type: cross Abstract: Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied

applicationsarxiv-cs-cv

KV-Control: Parameter-Efficient K/V Injection for Trajectory-Controlled Text-to-Motion

model-releasesarxiv-cs-cv

arXiv:2606.05624v1 Announce Type: new Abstract: Text-conditioned 3D human motion models now synthesize plausible motions from prompts, but practical animation and embodied-agent workflows rarely stop

3PoinTr: 3D Point Tracks for Learning Manipulation from Unconstrained Human Videos

arXiv:2603.08485v2 Announce Type: replace Abstract: Learning manipulation policies from human videos could greatly reduce the need for expensive robot demonstrations, but existing approaches typically

Local Ai

A Geometric View of Counterfactual Behavior: Interaction of Boundary Proximity and Local Support

arXiv:2606.04209v1 Announce Type: new Abstract: Counterfactual explanations seek small, semantically meaningful changes to an input that alter a model's prediction, and are widely used to interpret an

local-aiarxiv-cs-lg

AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors

arXiv:2509.21597v2 Announce Type: replace-cross Abstract: With the prevalence of artificial intelligence (AI)-generated content, such as audio deepfakes, a large body of recent work has focused on dev

GENEB: Why Genomic Models Are Hard to Compare

arXiv:2606.04525v1 Announce Type: new Abstract: Progress in genomic foundation models is difficult to assess due to fragmented benchmarks, incompatible evaluation protocols, and task-specific reportin

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

arXiv:2606.05015v1 Announce Type: new Abstract: World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet h

Multi-Granularity 3D Kidney Lesion Characterization from CT Volumes

arXiv:2606.04365v1 Announce Type: cross Abstract: Radiology reports describe kidney lesions by type, size, enhancement, and attenuation, yet existing 3D methods predict only at the patient or organ le

Physics-Informed Video Generation via Mixture-of-Experts Latent Alignment

model-releasesarxiv-cs-cv

arXiv:2606.04737v1 Announce Type: new Abstract: Large-scale video generation models have made remarkable progress in semantic consistency and visual quality, producing videos that are increasingly coh