In terms of using parameters that are possibly much smaller than degeneracy and never larger, there are two results that improve over degeneracy.
First, since the algorithm for degeneracy employs a reduction of the original instance with $n$ vertices to $n$ instances with at most $d+1$ vertices, one may get an algorithm with running time $O(1.28^{d-k})$ where $k$ is the clique size as follows: Reduce each of the $n$ many $k$-Clique instances to a $d'-k$-Vertex Cover instance with $d'\le d+1$ and then use the fastest parameterized algorithm for the Vertex Cover problem [1].
Second, there is an algorithm that enumerates all maximal cliques in $3^{\gamma /3} n^{O(1)}$ time [2]. Herein, the parameter $\gamma$ is called the weak closure of the input graph. It is the smallest number for which the following holds:
There is an ordering $(v_1, v_2, \ldots, v_n)$ of the vertices of the input graph in which every vertex $v_i$ has in $G[v_i,v_{i+1},\ldots,v_n]$ at most $\gamma-1$ common neighbors with every vertex $v_j$ that is not a neighbor of $v_i$.
This parameter is motivated by the observation that in social networks, vertices with many common neighbors tend to be adjacent. It can be easily seen that $\gamma\le d$ in every graph. Conversely, in a clique on $n$ vertices we have $\gamma=0$ and $d=n-1$.
[1] Chen, Jianer; Kanj, Iyad A.; Xia, Ge, Improved upper bounds for vertex cover, Theor. Comput. Sci. 411, No. 40-42, 3736-3756 (2010). ZBL1205.05217.
[2] Fox, Jacob; Roughgarden, Tim; Seshadhri, C.; Wei, Fan; Wein, Nicole, Finding cliques in social networks: a new distribution-free model, ZBL07206136.