Search: “pretraining”

KVNN: Learnable Multi-Kernel Volterra Neural Networks

arXiv:2604.15141v1 Announce Type: new Abstract: Higher-order learning is fundamentally rooted in exploiting compositional features. It clearly hinges on enriching the representation by more elaborate

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Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents

DGX agent

arXiv:2604.14717v1 Announce Type: cross Abstract: Persistent language-model agents increasingly combine tool use, tiered memory, reflective prompting, and runtime adaptation. In such systems, behavior

safetyarxiv-cs-lg

17 Apr 2026

Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

arXiv:2604.14206v1 Announce Type: new Abstract: This paper proposes a machine learning assisted portfolio optimization framework designed for low data environments and regime uncertainty. We construct

Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings

arXiv:2604.14547v1 Announce Type: new Abstract: Objective: Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Early prediction of P

Tutorials

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold

arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy

tutorialsarxiv-cs-ai

Retrieve, Then Classify: Corpus-Grounded Automation of Clinical Value Set Authoring

arXiv:2604.14616v1 Announce Type: new Abstract: Clinical value set authoring -- the task of identifying all codes in a standardized vocabulary that define a clinical concept -- is a recurring bottlene

Robustness of Vision Foundation Models to Common Perturbations

arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright

SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentation

arXiv:2604.15271v1 Announce Type: new Abstract: Reliable uncertainty estimation is critical for medical image segmentation, where automated contours feed downstream quantification and clinical decisio

Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation

arXiv:2604.14339v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation a

TokenLight: Precise Lighting Control in Images using Attribute Tokens

arXiv:2604.15310v1 Announce Type: new Abstract: This paper presents a method for image relighting that enables precise and continuous control over multiple illumination attributes in a photograph. We

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models

arXiv:2603.20997v2 Announce Type: replace Abstract: We identify a routing paradox in hybrid sequence models: content-based routing - deciding which tokens deserve expensive attention - requires pairwi

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model

arXiv:2604.05672v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often c

researcharxiv-cs-ro

Action Images: End-to-End Policy Learning via Multiview Video Generation

arXiv:2604.06168v2 Announce Type: replace Abstract: World action models (WAMs) have emerged as a promising direction for robot policy learning, as they can leverage powerful video backbones to model t

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Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding

arXiv:2604.13313v1 Announce Type: new Abstract: Vision-Language Models demonstrate remarkable capabilities but often struggle with compositional reasoning, exhibiting vulnerabilities regarding word or

Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET

arXiv:2406.12632v3 Announce Type: replace-cross Abstract: Positron emission tomography (PET) provides molecular biomarkers for Alzheimer's disease and related dementias (ADRD) and is increasingly used

Deep Spatially-Regularized and Superpixel-Based Diffusion Learning for Unsupervised Hyperspectral Image Clustering

arXiv:2604.13307v1 Announce Type: new Abstract: An unsupervised framework for hyperspectral image (HSI) clustering is proposed that incorporates masked deep representation learning with diffusion-base

DiffMagicFace: Identity Consistent Facial Editing of Real Videos

arXiv:2604.13841v1 Announce Type: new Abstract: Text-conditioned image editing has greatly benefitted from the advancements in Image Diffusion Models. However, extending these techniques to facial vid

F-Actor: Controllable Conversational Behaviour in Full-Duplex Models

arXiv:2601.11329v3 Announce Type: replace Abstract: Spoken conversational systems require more than accurate speech generation to have human-like conversations: to feel natural and engaging, they must

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

arXiv:2511.21760v3 Announce Type: replace Abstract: Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capabi

GeoBridge: A Semantic-Anchored Multi-View Foundation Model Bridging Images and Text for Geo-Localization

arXiv:2512.02697v3 Announce Type: replace Abstract: Cross-view geo-localization infers a location by retrieving geo-tagged reference images that visually correspond to a query image. However, the trad

Jump-Start Reinforcement Learning with Vision-Language-Action Regularization

arXiv:2604.13733v1 Announce Type: new Abstract: Reinforcement learning (RL) enables high-frequency, closed-loop control for robotic manipulation, but scaling to long-horizon tasks with sparse or imper

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Tutorials

Multitasking Embedding for Embryo Blastocyst Grading Prediction (MEmEBG)

arXiv:2604.13217v1 Announce Type: new Abstract: Reliable evaluation of blastocyst quality is critical for the success of in vitro fertilization (IVF) treatments. Current embryo grading practices prima

tutorialsarxiv-cs-cv

Native Hybrid Attention for Efficient Sequence Modeling

arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal

researcharxiv-cs-cl

Local Ai

Simplicity Prevails: The Emergence of Generalizable AIGI Detection in Visual Foundation Models

arXiv:2602.01738v2 Announce Type: replace Abstract: While specialized detectors for AI-Generated Images (AIGI) achieve near-perfect accuracy on curated benchmarks, they suffer from a dramatic performa

local-aiarxiv-cs-cv

Training-Free Semantic Multi-Object Tracking with Vision-Language Models

arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact

UNRIO: Uncertainty-Aware Velocity Learning for Radar-Inertial Odometry

model-releasesarxiv-cs-ro

arXiv:2604.13584v1 Announce Type: new Abstract: We present UNRIO, an uncertainty-aware radar-inertial odometry system that estimates ego-velocity directly from raw mmWave radar IQ signals rather than

VGGT-Segmentor: Geometry-Enhanced Cross-View Segmentation

arXiv:2604.13596v1 Announce Type: new Abstract: Instance-level object segmentation across disparate egocentric and exocentric views is a fundamental challenge in visual understanding, critical for app

ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body

arXiv:2512.14234v2 Announce Type: replace Abstract: Human communication is inherently multimodal and social: words, prosody, and body language jointly carry intent. Yet most prior systems model human

CLAD: Efficient Log Anomaly Detection Directly on Compressed Representations

arXiv:2604.13024v1 Announce Type: new Abstract: The explosive growth of system logs makes streaming compression essential, yet existing log anomaly detection (LAD) methods incur severe pre-processing

Combating Pattern and Content Bias: Adversarial Feature Learning for Generalized AI-Generated Image Detection

arXiv:2604.12353v1 Announce Type: new Abstract: In recent years, the rapid development of generative artificial intelligence technology has significantly lowered the barrier to creating high-quality f

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Cross-Domain Transfer with Particle Physics Foundation Models: From Jets to Neutrino Interactions

arXiv:2604.12364v1 Announce Type: cross Abstract: Future AI-based studies in particle physics will likely start from a foundation model to accelerate training and enhance sensitivity. As a step toward

Curvelet-Based Frequency-Aware Feature Enhancement for Deepfake Detection

arXiv:2604.12028v1 Announce Type: cross Abstract: The proliferation of sophisticated generative models has significantly advanced the realism of synthetic facial content, known as deepfakes, raising s

researcharxiv-cs-ai

Do Transformers Use their Depth Adaptively? Evidence from a Relational Reasoning Task

arXiv:2604.12426v1 Announce Type: cross Abstract: We investigate whether transformers use their depth adaptively across tasks of increasing difficulty. Using a controlled multi-hop relational reasonin

researcharxiv-cs-cl

Local Ai

Domain-Specific Latent Representations Improve the Fidelity of Diffusion-Based Medical Image Super-Resolution

arXiv:2604.12152v1 Announce Type: cross Abstract: Latent diffusion models for medical image super-resolution universally inherit variational autoencoders designed for natural photographs. We show that

local-aiarxiv-cs-ai

DPC-VQA: Decoupling Quality Perception and Residual Calibration for Video Quality Assessment

arXiv:2604.12813v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown promising performance on video quality assessment (VQA) tasks. However, adapting them to new

Generative Anonymization in Event Streams

arXiv:2604.12803v1 Announce Type: new Abstract: Neuromorphic vision sensors offer low latency and high dynamic range, but their deployment in public spaces raises severe data protection concerns. Rece

GeoAlign: Geometric Feature Realignment for MLLM Spatial Reasoning

arXiv:2604.12630v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have exhibited remarkable performance in various visual tasks, yet still struggle with spatial reasoning. Rec

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Grasp in Gaussians: Fast Monocular Reconstruction of Dynamic Hand-Object Interactions

arXiv:2604.12929v1 Announce Type: new Abstract: We present Grasp in Gaussians (GraG), a fast and robust method for reconstructing dynamic 3D hand-object interactions from a single monocular video. Unl

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Invariant Features for Global Crop Type Classification

model-releasesarxiv-cs-lg

arXiv:2509.03497v3 Announce Type: replace Abstract: Accurate global crop type mapping supports agricultural monitoring and food security, yet remains limited by the scarcity of labeled data in many re

iTeach: In the Wild Interactive Teaching for Failure-Driven Adaptation of Robot Perception

model-releasesarxiv-cs-ro

arXiv:2410.09072v4 Announce Type: replace Abstract: Robotic perception models often fail when deployed in real-world environments due to out-of-distribution conditions such as clutter, occlusion, and

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

researcharxiv-cs-ai

Point Prompting: Counterfactual Tracking with Video Diffusion Models

arXiv:2510.11715v2 Announce Type: replace Abstract: Trackers and video generators solve closely related problems: the former analyze motion, while the latter synthesize it. We show that this connectio

PromptEcho: Annotation-Free Reward from Vision-Language Models for Text-to-Image Reinforcement Learning

model-releasesarxiv-cs-ai

arXiv:2604.12652v1 Announce Type: cross Abstract: Reinforcement learning (RL) can improve the prompt following capability of text-to-image (T2I) models, yet obtaining high-quality reward signals remai

Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprinting

arXiv:2604.12834v1 Announce Type: cross Abstract: Radio frequency fingerprints (RFFs) enable secure wireless authentication but struggle in open-set scenarios with unknown devices and varying channels

Scaffold-Conditioned Preference Triplets for Controllable Molecular Optimization with Large Language Models

arXiv:2604.12350v1 Announce Type: cross Abstract: Molecular property optimization is central to drug discovery, yet many deep learning methods rely on black-box scoring and offer limited control over

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Schema-Adaptive Tabular Representation Learning with LLMs for Generalizable Multimodal Clinical Reasoning

arXiv:2604.11835v1 Announce Type: cross Abstract: Machine learning for tabular data remains constrained by poor schema generalization, a challenge rooted in the lack of semantic understanding of struc

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SOAR: Self-Correction for Optimal Alignment and Refinement in Diffusion Models

arXiv:2604.12617v1 Announce Type: cross Abstract: The post-training pipeline for diffusion models currently has two stages: supervised fine-tuning (SFT) on curated data and reinforcement learning (RL)

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Local Ai

TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs

arXiv:2602.18109v2 Announce Type: replace Abstract: Real-time schedulers must reason about tight deadlines under strict compute budgets. We present TempoNet, a reinforcement learning scheduler that pa

local-aiarxiv-cs-lg