1. Introduction  
2. Definitions, notation, and background  
3. Additive matrix binding  
3.1. Matrix binding as writing to “slots” in superposition  
3.2. Tree representations using matrices  
3.3. Feature multiplicity in additive models  
4. Multi-token mechanisms  
4.1. Syntactic relations and tree embeddings  
4.2. Reference mechanisms: pointers and identifiers  
5. Vector symbolic architecture  
5.1. Tensor constructions  
5.2. Binary vectors  
5.3. Is VSA a plausible mechanism for real neural nets?  
5.4. Implications for the search for features  
6. Conclusion and future work