As someone who has stared at arXiv TeX/LaTeX for years, I can testify you don't want to be looking at TeX math in actual latex documents, there is a lot more that goes in there beyond the toy formula syntax used on the web.
As also someone who has worked on math search engines and math-rich NLP for a few years, complaining that you have a structured machine-parseable representation for mathematics and wanting TeX instead sounds naive. On one hand, the MathML formulas in the datasets already could preserve the source TeX (the TeX annotations may even be there, I can't remember right now), should you need it directly. On the other hand, you can use any structured methods, such as the ones used by content-based search engines such as MathWebSearch, or handpick any relevant information from the MathML tree to feed it back into a statistical algorithm, as done for example by the WebMIAS search engine.
The most fundamental bit to understand if you're doing research on automated processing of human mathematics is that formulas are two dimensional objects best represented as trees, be they layout trees describing the presentation, or operator trees describing the content, or some other hybrid tree that tries doing both (such as LaTeXML's XMath spec).