arXiv Machine Learning
Jul 17
Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality
arXiv:2607. 14721v1 Announce Type: cross Abstract: Cross-modal learning, i.
Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality
Cross-modal learning, i. e.
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Jul 13
Mixture of Probes: Learning from Privileged Modalities in Multimodal LLMs Through Probing
arXiv:2607. 08839v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are typically designed under the assumption that all modalities available during training will also be accessible at inference.
arXiv Machine Learning
Jul 2
Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning
arXiv:2505. 19614v2 Announce Type: replace Abstract: Multimodal learning has seen remarkable progress, particularly with large-scale pre-training across various modalities.
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Jul 7
K9-Bench: Evaluating Multimodal LLMs on Canine-Centric Videos
arXiv:2607. 02680v1 Announce Type: cross Abstract: MLLMs have shown strong zero-shot capabilities across diverse inputs such as across images, video, audio, and text.
arXiv Machine Learning
Jul 7
Beyond Modality Fusion: Deep Ensembles for Multimodal Classification
arXiv:2607. 05019v1 Announce Type: new Abstract: In multimodal classification, late-fusion approaches classify concatenated modality-specific features extracted by unimodal neural networks.
arXiv Machine Learning
Jun 5
Is Diversity All You Need for Scalable Robotic Manipulation?
arXiv:2507. 06219v2 Announce Type: replace-cross Abstract: Data scaling has driven remarkable success in foundation models for Natural Language Processing (NLP) and Computer Vision (CV), yet the principles of effective data scaling in robotic manipulation remain insufficiently understood.
arXiv AI
Jun 11
Information-Theoretic Decomposition for Multimodal Interaction Learning
arXiv:2606. 11614v1 Announce Type: cross Abstract: Multimodal learning hinges on capturing redundant, unique, and synergistic information across modalities, which collectively constitute multimodal interactions.
arXiv AI
Jul 8
MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning
arXiv:2409. 06067v3 Announce Type: replace Abstract: Previous studies on federated learning (FL) often encounter performance degradation due to data heterogeneity among different clients.
arXiv Machine Learning
Aug 6
Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes
arXiv:2608. 05000v1 Announce Type: cross Abstract: Vision offers a critical axis for advancing foundation models, driving a shift towards natively unified multimodal pretraining.
arXiv Machine Learning
Aug 4
DataClaw0: Agentic Tailoring Multimodal Data from Raw Streams
arXiv:2606. 21337v2 Announce Type: replace Abstract: Raw multimodal streams are abundant but noisy, redundant, and unaligned with any particular training objective.
arXiv AI
Aug 5
Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent
arXiv:2608. 03979v1 Announce Type: cross Abstract: We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense spatiotemporal grounding coupled with open-web exploration.
arXiv Machine Learning
Jul 28
Self-Distillation of Hidden Layers for Self-Supervised Representation Learning
arXiv:2603. 15553v2 Announce Type: replace-cross Abstract: The landscape of self-supervised learning (SSL) is currently dominated by generative approaches (e.