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20242026
most citedLow-Rank Adaptation for Foundation Models: A Comprehensive Review

9 citations · 23 across the 21 of their papers we have counts for

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Showing 2025 · cs.LGShow all

7 papers · 2 filters

cs.LG2025★ 4 cited

Hyperbolic Deep Learning for Foundation Models: A Survey

Neil He, Hiren Madhu, Ngoc Bui +2

Foundation models pre-trained on massive datasets, including large language models (LLMs), vision-language models (VLMs), and large multimodal models, have demonstrated remarkable…

cs.LG2025

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning

Ngoc Bui, Menglin Yang, Runjin Chen +5

Backward compatible representation learning enables updated models to integrate seamlessly with existing ones, avoiding to reprocess stored data. Despite recent advances, existing…

cs.LG2025

HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts

Neil He, Rishabh Anand, Hiren Madhu +5

Large language models (LLMs) have shown great success in text modeling tasks across domains. However, natural language exhibits inherent semantic hierarchies and nuanced geometric…

cs.LG2025

HyperCore: The Core Framework for Building Hyperbolic Foundation Models with Comprehensive Modules

Neil He, Menglin Yang, Rex Ying

Hyperbolic neural networks have emerged as a powerful tool for modeling hierarchical data across diverse modalities. Recent studies show that token distributions in foundation mode…

cs.LG2025★ 1 cited

Position: Beyond Euclidean -- Foundation Models Should Embrace Non-Euclidean Geometries

Neil He, Jiahong Liu, Buze Zhang +6

In the era of foundation models and Large Language Models (LLMs), Euclidean space has been the de facto geometric setting for machine learning architectures. However, recent litera…

cs.LG2025

Lorentzian Residual Neural Networks

Neil He, Menglin Yang, Rex Ying

Hyperbolic neural networks have emerged as a powerful tool for modeling hierarchical data structures prevalent in real-world datasets. Notably, residual connections, which facilita…

cs.LG2025★ 9 cited

Low-Rank Adaptation for Foundation Models: A Comprehensive Review

Menglin Yang, Jialin Chen, Jinkai Tao +9

The rapid advancement of foundation modelslarge-scale neural networks trained on diverse, extensive datasetshas revolutionized artificial intelligence, enabling unprecedented advan…