CNM: An Interpretable Complex-valued Network for Matching
read the original abstract
This paper seeks to model human language by the mathematical framework of quantum physics. With the well-designed mathematical formulations in quantum physics, this framework unifies different linguistic units in a single complex-valued vector space, e.g. words as particles in quantum states and sentences as mixed systems. A complex-valued network is built to implement this framework for semantic matching. With well-constrained complex-valued components, the network admits interpretations to explicit physical meanings. The proposed complex-valued network for matching (CNM) achieves comparable performances to strong CNN and RNN baselines on two benchmarking question answering (QA) datasets.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Training-Free Quantum Generative Paradigm via Local Parent Hamiltonians
A training-free quantum generative paradigm is proposed that encodes target distributions as ground states of constructed local parent Hamiltonians for image and text generation.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.