On tensor products of "generic" vectors Suppose that $x_1,\ldots,x_n$ are $n$ vectors in $\mathbb{R}^m$ (where $m<n\leq m^2$) such that any subset of $m$ of them are linearly independent (i.e., they are "generic"). Now, form the $m^2\times n$ matrix 
$A = [x_1\otimes x_1, x_2\otimes x_2,\cdots,x_n\otimes x_n]$ (where $\otimes$ is the tensor product or the Kronecker product)
Is there a nice way of showing that this matrix is full rank (i.e., rank$(A)=n$)?

Edit: (after the great answers below)


*

*The statement, as I asked, was shown to be false by Clement de Seguins Pazzi with a very nice argument. 

*The statement that I had hoped to ask is true and the details can be found in Dustin Mixon's answers

 A: The result is not true and the best upper-bound on $n$ to make it work happens to 
be $2m-1$. 
Assume that $n<2m$. Let $(t_1,\dots,t_n)$ be a family of real numbers
such that $\sum_{k=1}^n t_k \,x_k \otimes x_k=0$. Assume that some $t_k$ is non-zero. 
Denote by N the number of indices $k$ such that $t_k \neq 0$. 
Obviously $N>m$. Without loss of generality, we may assume that $t_1,\dots,t_m$ are all non-zero, and we rewrite the above equality as 
$\sum_{k=1}^m t_k x_k \otimes x_k=-\sum_{k=m+1}^n t_k x_k \otimes x_k$. 
As $(x_1,\dots,x_m)$ and $(x_{m+1},\dots,x_n)$ are both linearly independent, 
one sees that the rank of $\sum_{k=1}^m t_k x_k \otimes x_k$ is $m$, whereas the one of
$\sum_{k=m+1}^n t_k\,x_k \otimes x_k$ is at most $n-m<m$. This is a contradiction. 
To see that $2m-1$ is an optimal upper-bound, note first that
the problem may be entirely restated in terms of families of symmetric rank $1$ matrices. One takes a family $(X_i)_{1 \leq i \leq n}$ of vectors of $\mathbb{R}^m$
in which every subfamily with $m$ vectors is a basis of $\mathbb{R}^m$, 
and one tries to find the rank of the family $(X_i X_i^T)_{1 \leq i \leq n}$ of
rank $1$ symmetric matrices.
Now, for $a \in \mathbb{R}$, consider the vector $X(a)=(a^k)_{0 \leq k \leq n-1}$. 
Then, for every $n$-tuple $(a_1,\dots,a_n)$ of real numbers, the vectors 
$X(a_1),\dots,X(a_n)$ are linearly independent; however, the matrices $X(a)X(a)^T$
all belong to the space of real $m \times m$ Hankel matrices, which has dimension $2m-1$, 
and hence a family consisting of such matrices has rank at most $2m-1$. 
A: The result you want is that $m(m+1)/2$ generic vectors in $\mathbb{R}^m$ have linearly independent outer products (as do $m^2$ generic vectors in $\mathbb{C}^m$). These results are indeed true; see Theorem 2.1 in this paper. EDIT: The notion of generic here is not the same as yours. I'll sketch the proof, since you might not be familiar with frame theory jargon:
First show that such ensembles exist. To do this, pick a basis for the space of symmetric (self-adjoint, if the vectors are complex) matrices. Use the spectral theorem to decompose each basis element into outer products. Now you have a bunch of outer products that span the space, meaning it contains a basis. As such, there exists a basis composed solely of outer products.
To show that a generic choice of vectors have outer products which form a basis, vectorize the outer products in terms of some basis of the space, and make them the columns of a square matrix $A$. The determinant of $A$ is a polynomial of the real and imaginary parts of the entries of the original vectors, and since there exists a collection of vectors at which this polynomial is nonzero (by the previous discussion), this polynomial must be nonzero. As such, the complement of this polynomial's variety is dense with full measure, i.e., a generic choice of vectors will make $A$ have nonzero determinant, and so the outer products will be linearly independent, as desired.
EDIT: Your particular notion of generic is treated in Proposition 4.1 of the same paper. Specifically, your condition (that the vectors are "full spark") implies the outer products are independent provided $n\leq 2m-1$.
A: The following tries to be a lower bound of the rank, complementing the answer of 
Clément de Seguins Pazzi.
You can assume that all $X_i$ are normed and use Euclidean $\mathbb R^m$. Then $X_i.X_i^T$ is the orthonormal projection onto the line through $X_i$. All these orthoprojections describe $\mathbb RP^{m-1}$ smoothly embedded into $End(\mathbb R^m)$. 
There is a conjecture that the minimal $N$ where you can embed $P^{m-1}$ is $N=2(m-1) -\alpha(m-1) +1$ where $\alpha(k)$ is the number of 1's in the dyadic expansion of $k$. Thus you can find $N$ vectors such the rank is $N$, if this conjecture is true.
This might be a horribly involved not-yet-proof of a possibly simple fact.  
Edit: Dustin G. Mixon's answer shows that the dimension of the span of $P^{m-1}$ embedded in $End(\mathbb R^m)$ is $m(m+1)/2$.
