Search: “pretraining”

ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Cross-Modal Alignment Dataset

arXiv:2505.10083v2 Announce Type: replace Abstract: Conventional forecasting methods are trained end-to-end on unimodal time series, which limits their ability to exploit textual information and under

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Model Releases

CoRe-WAM: Correspondence-Aligned Temporal Residuals for World Action Models

DGX agent

arXiv:2609.27314v1 Announce Type: new Abstract: Comparing current and past observations helps robots understand scene changes and select subsequent actions during manipulation. However, comparing visu

model-releasesarxiv-cs-ro

24 Sept 2026

FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

arXiv:2609.27710v1 Announce Type: new Abstract: Pathology vision-language foundation models vary in performance across diseases and tasks, with no single model consistently performing best. The high c

safetyarxiv-cs-cv

Geometry-Conditioned Visual Place Recognition in Natural Environments

arXiv:2609.27370v1 Announce Type: cross Abstract: Visual Place Recognition (VPR) in natural environments remains challenging due to repetitive vegetation, sparse distinctive landmarks, and substantial

Memory That Changes Action Is Not Memory That Guides It: Counterfactual Auditing of History-Conditioned Robot Policies

arXiv:2609.27247v1 Announce Type: new Abstract: A robot returning a block to its origin tray may encounter two task-consistent pasts that reconverge to the same current input but warrant different act

safetyarxiv-cs-ro

Multimodal Voice Activity Projection for Social Robot Mediation: Expected Behavior and Deployment Constraints

arXiv:2609.28317v1 Announce Type: new Abstract: Turn-taking prediction is especially relevant for social robots that act as mediators in human-human interaction, where the expected action is often not

researcharxiv-cs-ro

Local Ai

nnFoundation: 3D Foundation Models for Radiology

arXiv:2609.26924v1 Announce Type: new Abstract: Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shif

local-aiarxiv-cs-cv

The Gaussian Is Enough: Flow-Matching Priors Do Not Help When Fine-Tuning Large Behavior Models

arXiv:2609.27070v1 Announce Type: cross Abstract: Modern robot imitation learning increasingly relies on generative policies based on diffusion or flow-matching models, which generate actions by trans

researcharxiv-cs-ai

PreGS: A Parameter-Transfer-Based Multi-Expert Graph Neural Network for Node Classification

arXiv:2609.26310v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance in node classification by aggregating information from graph neighborhoods. However, a single agg

23 Sept 2026

TRACE: Transparent Retrieval for Abstract Concept Evaluation

arXiv:2609.26168v1 Announce Type: cross Abstract: Recent work reports that vision--language models (VLMs) struggle to establish and maintain stable reference in repeated reference games. Rather than a

23 Sept 2026

Beetle: A Bilingual Model Suite for Modelling Second-Language Processing

arXiv:2609.22633v1 Announce Type: new Abstract: Bilingual language models (LMs) offer a controlled setting for studying how training conditions shape second-language (L2) behaviour, but prior work typ

safetyarxiv-cs-cl

Tutorials

Common Cause, Not Cross-Attention: Blocking Visual Shortcuts in Audio-Video Generation

arXiv:2609.22361v1 Announce Type: new Abstract: Joint audio--video generators are trained on data in which what an event looks like and what it sounds like are strongly, often spuriously, correlated:

tutorialsarxiv-cs-lg

Comparative Analysis of State-of-the-Art Foundation Models for Sleep Analysis Under Channel Reduction

arXiv:2609.22105v1 Announce Type: cross Abstract: Automatic sleep staging from polysomnography (PSG) is a well-studied task, but PSG itself is expensive, clinic-based, and burdensome to manually score

Comparative Performance and Parameter-Efficient Adaptation of DINOv2 for Active Trachoma Classification

arXiv:2609.23832v1 Announce Type: new Abstract: Automated grading of conjunctival photographs could reduce the cost and variability of trachoma prevalence surveys, but the relative value of modern pre

Local Ai

D-JEPA: A Decision-Aligned Latent World Model

arXiv:2609.24749v1 Announce Type: cross Abstract: Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will

local-aiarxiv-cs-lg

'Dear LLaVA, Please Drive': A Depth-Aware Vision-Language Agent for Closed-Loop Robotic Control

model-releasesarxiv-cs-ro

arXiv:2609.22925v1 Announce Type: new Abstract: Vision-language models (VLMs) provide a compelling foundation for reasoning-driven mobile navigation, offering rich contextual understanding and strong

Hardware

G6D: Geometric Learning-Free RGB-D 6D Pose Solver for Robotic Manipulation

arXiv:2609.23566v1 Announce Type: new Abstract: 6D object pose estimation is fundamental to robotic manipulation and automation. Recent zero-shot methods have significantly improved generalization to

hardwarearxiv-cs-cv

Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models

arXiv:2609.24879v1 Announce Type: new Abstract: Counterfactual image generation answers questions about how a subject would have looked under retrospective, hypothetical scenarios. Recent methods have

Applications

MUSE: Dependency-Aware Adaptation of a Frozen Vision Backbone for Multivariate Time Series Forecasting

arXiv:2609.24441v1 Announce Type: new Abstract: Multivariate time-series forecasting is essential to many real-world applications. Recent large vision models (LVMs) offer a promising paradigm by trans

applicationsarxiv-cs-lg

Optimizers for Diffusion Models: A Controlled Benchmark

arXiv:2609.23055v1 Announce Type: new Abstract: Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far

Replicating the Geometry of Emotion Representations in a Base Open-Weights Model

model-releasesarxiv-cs-cl

arXiv:2609.22208v1 Announce Type: new Abstract: Sofroniew et al. (2026) report that emotion concepts in Claude Sonnet 4.5 are represented as vectors whose geometry mirrors human affect psychology. We

Scaling Sim-to-Real VLA Reinforcement Learning with Generative 3D Worlds

arXiv:2603.18532v3 Announce Type: replace-cross Abstract: The strong performance of large vision-language models (VLMs) trained with reinforcement learning (RL) has motivated similar approaches for fi

safetyarxiv-cs-lg

ToneCL: Contrastive Learning for Few-Shot Syllable-Level Tone Classification

arXiv:2609.24903v1 Announce Type: new Abstract: Tone languages constitute over 50-70% of the world's languages, but the vast majority are low-resource, lacking the large transcribed corpora needed for

researcharxiv-cs-cl

Agents

Towards robust multimodal 3D object detection via visual foundation models

arXiv:2609.23541v1 Announce Type: new Abstract: Multimodal 3D object detection is fundamental to robust perception in autonomous driving because it integrates complementary information from LiDAR and

agentsarxiv-cs-cv

MOSAIC-SR: Transformer-Guided Symbolic Regression for Scientific Equation Recovery

arXiv:2609.20997v1 Announce Type: new Abstract: Symbolic regression aims to recover closed-form equations from observations, providing interpretable models for scientific discovery. Existing approache

Reconstruction of 4D Mitral Regurgitation Hemodynamics from Sparse Planar Data using Deep Operator Networks with Test-Time Adaptation

arXiv:2609.20857v1 Announce Type: cross Abstract: Quantifying mitral regurgitation severity remains limited by the assumptions of clinical flow convergence methods, while high-fidelity simulation and

SFVO: Decoupled Confidence-Guided Stereo-Flow Visual Odometry with Bidirectional PnP

arXiv:2609.21754v1 Announce Type: new Abstract: Deep learning-based visual odometry (VO) has achieved significant progress, yet most existing methods focus on a monocular approach, which suffers from

Towards the Vision-Sound-Language-Action Paradigm: The HEAR Framework for Sound-Centric Manipulation

arXiv:2603.16086v2 Announce Type: replace-cross Abstract: While recent Vision-Language-Action (VLA) models have begun to incorporate audio, they typically treat sound as static pre-execution prompts o

Tracing the Evidence Behind Zero-Shot Time-Series Forecasting: A Source-First Taxonomy and Audit Framework

arXiv:2609.21425v1 Announce Type: new Abstract: Zero-shot time-series forecasting (TSF) is often described as forecasting without target-specific parameter updates, but that training-status condition

Local Ai

Automated Goldsmith's Mark Retrieval in Silverware

arXiv:2609.20509v1 Announce Type: new Abstract: For art historians, goldsmith marks play a critical role in the identification and dating of artifacts. In practice, experts must manually compare a que

local-aiarxiv-cs-cv

FreqCondNorm: Towards Cross-domain Predictive Maintenance through a Frequency-Conditioned Transformer Foundation Model

arXiv:2609.20535v1 Announce Type: new Abstract: Deep learning predictive maintenance models suffer from poor transferability across machines and operating conditions, especially when labelled data are

researcharxiv-cs-ai

Generalization through Lexical Abstraction in Transformer Models: The Case of Functional Words

arXiv:2609.19887v1 Announce Type: new Abstract: Pronouns, adverbs and other functional words (such as they, her, somewhere, there) are often used in language to replace concrete nouns or phrases, when

researcharxiv-cs-cl

Lens: Bringing the Right Semantic Perspective into Focus for Training-Free Multimodal Representation Learning

arXiv:2609.20252v1 Announce Type: cross Abstract: High-quality representations are essential for a wide range of downstream tasks. Dedicated embedding models are explicitly optimized for representatio

Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings

arXiv:2609.19230v1 Announce Type: new Abstract: Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when devi

researcharxiv-cs-cv

Visual Sim-to-Real Learning for Robotic Insertion under Geometric Variations: Application to Rebar Installation

arXiv:2609.20477v1 Announce Type: new Abstract: Rebar insertion is among the most repetitive and physically demanding tasks on construction sites, and a contact-rich problem at 1.4 mm clearance. The p

safetyarxiv-cs-ro

Exact semantic readout from compressed vector representations

arXiv:2609.18047v1 Announce Type: new Abstract: We characterize when compressed vector representations admit exact linear or affine readouts of a finite lexicon's truth conditions: one fixed map per p

researcharxiv-cs-cl

Instrument Classification of Solo Sheet Music Images

arXiv:2609.18980v1 Announce Type: cross Abstract: This paper studies instrument classification of solo sheet music. Whereas previous work has focused on instrument recognition in audio data, we instea

Robust and Efficient AI Frameworks for Scalable Material Design and Property Prediction

arXiv:2609.17646v1 Announce Type: cross Abstract: This thesis develops robust and efficient AI frameworks for accelerating crystalline materials discovery by addressing both major stages of the materi

STRADAViT: Self-Supervised Domain Adaptation of Vision Transformer Backbones for Radio Astronomy

arXiv:2603.29660v4 Announce Type: replace-cross Abstract: Next-generation radio astronomy surveys are delivering millions of resolved sources, yet scalable morphology analysis remains difficult across

researcharxiv-cs-cv

Track, Articulate, Act: Generating Articulation from Casual Human Videos

arXiv:2609.19119v1 Announce Type: new Abstract: Human videos contain rich causal evidence for robot manipulation: they reveal how hand motion induces object motion and produces task-relevant changes i

researcharxiv-cs-cv

Where Grokking Happens: Distributed Utility and Fourier Recoding Without a Module Switch

arXiv:2609.17571v1 Announce Type: cross Abstract: Where in a Transformer is the change from memorization to generalization functionally expressed? We introduce Transition Games--behavior-aligned exact

safetyarxiv-cs-ai

Continuous-Time Machine Learning: A Unified Mathematical Perspective

arXiv:2609.16710v1 Announce Type: cross Abstract: Continuous-time (CT) machine learning has emerged as a principled framework for modeling temporal dynamics as a continuous process, particularly when

Tutorials

High-Fidelity Video Quality Assessment with VQA-Specific Saliency

arXiv:2609.16946v1 Announce Type: new Abstract: No-reference video quality assessment (NR VQA) has recently seen promising progress with deep learning. However, video data is inherently large, and pro

tutorialsarxiv-cs-cv

HyCoSeq: Contextual Hyperbolic Representation Learning for Genomic Sequences

arXiv:2609.16925v1 Announce Type: new Abstract: Hyperbolic geometry provides a natural inductive bias for genomic representation learning, but existing hyperbolic genomic models primarily use Lorentz

safetyarxiv-cs-lg

Hyper-RED: Scalable Event Pre-training via Semantic Hypergraph Distillation

arXiv:2609.16811v1 Announce Type: new Abstract: Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity

safetyarxiv-cs-cv

IL-ACT: Imitation Learning with Adaptive Cartesian Tracking Control for a 30-ton Excavator

arXiv:2609.16696v1 Announce Type: new Abstract: Autonomous excavator control is challenged by coupled kinematics, actuation lag, and uncertainty. We propose imitation learning and adaptive Cartesian t

safetyarxiv-cs-ro

LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence

arXiv:2609.17488v1 Announce Type: new Abstract: We introduce LimiX-2, a new model in the LimiX family, developed through model and data scaling guided by our previously established scaling laws. LimiX

Applications

Modality-Autoregressive World-Action Models

arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as

applicationsarxiv-cs-ro