Is there any kind of formal or empirical validation of the information that the paper contains? Citations and peer-reviews are standard today, as well as the reputation of the venue. Trust is often correlated with these, but this leads to the perversion of the whole system.
Many systems pervert when there is some discrepancy between how things are and how they look. E.g. economic bubbles, perceived and real value of some goods.
IMHO, trustworthiness comes from verifiability (and I think that is the whole point of science). Verifiability implies replicability, reproducibility, falsifiability, etc.
In short: no, you should not trust a paper that doesn't cite any previous work, but you should not trust a paper that cites many others just because they are there. You should, in general, trust no one, and check whether what they say is true by yourself, whether it is coherent with latter studies, whether latter studies could have contradicted it, whether it is possible to see if what they claim is true or not (open data, open science, open source, etc.)
Related and recommended: Top Ten Reasons to Not Share Your Code
(and why you should anyway)
PD: a whole different point (as pointed by @petelclark) is evaluating a paper, in that case you have to consider whether what the paper says is true, but you have to check as well whether it is original research (or it was published before). Citations help to understand the context and the state of the art previous to the paper, and to see that the authors know the state of the art.