  Proving super polynomial size lower bounds for various classes of arithmetic
circuits computing explicit polynomials is a very important and challenging
task in algebraic complexity theory. We study representation of polynomials as
sums of weaker models such as read once formulas (ROFs) and read once oblivious
algebraic branching programs (ROABPs). We prove:
  (1) An exponential separation between sum of ROFs and read-$k$ formulas for
some constant $k$. (2) A sub-exponential separation between sum of ROABPs and
syntactic multilinear ABPs.
  Our results are based on analysis of the partial derivative matrix under
different distributions. These results highlight richness of bounded read
restrictions in arithmetic formulas and ABPs.
  Finally, we consider a generalization of multilinear ROABPs known as
strict-interval ABPs defined in [Ramya-Rao, MFCS2019]. We show that
strict-interval ABPs are equivalent to ROABPs upto a polynomial size blow up.
In contrast, we show that interval formulas are different from ROFs and also
admit depth reduction which is not known in the case of strict-interval ABPs.
