Fusion Anything: A Generalized Multimodal Foundation Model

arXiv:2609.22107 · cs.LG, cs.CL · Submitted 2026-08-16 · Read on arXiv

cs.LG, cs.CL

Submitted: 2026-08-16

Updated: 2026-09-30

Code: https://github.com/MrLinNing/MemristorLSM

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Foundation Model — 33× in this paper · explained in 3 episodes
• Multimodal Dataset — 30× in this paper · explained in 2 episodes
• AUC — 19× in this paper · explained in 2 episodes
• Feature Extraction — 18× in this paper · explained in 2 episodes
• Multimodal Fusion — 18× in this paper · explained in 3 episodes
• Adaptation — 14× in this paper · explained in 1 episode
• Multimodal Learning — 11× in this paper · explained in 2 episodes
• Foundation Models — 9× in this paper · explained in 7 episodes
• In-Context Learning — 9× in this paper · explained in 4 episodes
• Actor — 5× in this paper · explained in 3 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Transformer — 5× in this paper · explained in 2 episodes
• Attention Mechanism — 4× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Aggregation Function — 3× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Structural Multimodal Causal Model — 2× in this paper
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Affective Computing — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Correlation Control Module — 1× in this paper
• Cross-Attention Mechanism — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes

Sources

• On the Opportunities and Risks of Foundation Models
• LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models
• MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning
• Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers
• LoRA: Low-Rank Adaptation of Large Language Models

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