10 citations · 15 across the 2 of their papers we have counts for
4 papers
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil +3
State-Space Models (SSMs), and particularly Mamba, have recently emerged as a promising alternative to Transformers. Mamba introduces input selectivity to its SSM layer (S6) and in…
Approximately Equivariant Graph Networks
Ningyuan Huang, Ron Levie, Soledad Villar
Graph neural networks (GNNs) are commonly described as being permutation equivariant with respect to node relabeling in the graph. This symmetry of GNNs is often compared to the tr…
From Local to Global: Spectral-Inspired Graph Neural Networks
Ningyuan Huang, Soledad Villar, Carey E. Priebe +4
Graph Neural Networks (GNNs) are powerful deep learning methods for Non-Euclidean data. Popular GNNs are message-passing algorithms (MPNNs) that aggregate and combine signals in a…
Endowing Language Models with Multimodal Knowledge Graph Representations
Ningyuan Huang, Yash R. Deshpande, Yibo Liu +4
We propose a method to make natural language understanding models more parameter efficient by storing knowledge in an external knowledge graph (KG) and retrieving from this KG usin…