diff -r eb2f9d453070 -r 1c978b5bcc65 doc/groups.dox
--- a/doc/groups.dox	Sat Mar 16 14:11:32 2013 +0100
+++ b/doc/groups.dox	Mon Mar 18 17:41:19 2013 +0100
@@ -317,7 +317,7 @@
 
 This group contains the common graph search algorithms, namely
 \e breadth-first \e search (BFS) and \e depth-first \e search (DFS)
-\ref clrs01algorithms.
+\cite clrs01algorithms.
 */
 
 /**
@@ -326,7 +326,7 @@
 \brief Algorithms for finding shortest paths.
 
 This group contains the algorithms for finding shortest paths in digraphs
-\ref clrs01algorithms.
+\cite clrs01algorithms.
 
  - \ref Dijkstra algorithm for finding shortest paths from a source node
    when all arc lengths are non-negative.
@@ -348,7 +348,7 @@
 \brief Algorithms for finding minimum cost spanning trees and arborescences.
 
 This group contains the algorithms for finding minimum cost spanning
-trees and arborescences \ref clrs01algorithms.
+trees and arborescences \cite clrs01algorithms.
 */
 
 /**
@@ -357,7 +357,7 @@
 \brief Algorithms for finding maximum flows.
 
 This group contains the algorithms for finding maximum flows and
-feasible circulations \ref clrs01algorithms, \ref amo93networkflows.
+feasible circulations \cite clrs01algorithms, \cite amo93networkflows.
 
 The \e maximum \e flow \e problem is to find a flow of maximum value between
 a single source and a single target. Formally, there is a \f$G=(V,A)\f$
@@ -373,13 +373,13 @@
 
 LEMON contains several algorithms for solving maximum flow problems:
 - \ref EdmondsKarp Edmonds-Karp algorithm
-  \ref edmondskarp72theoretical.
+  \cite edmondskarp72theoretical.
 - \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm
-  \ref goldberg88newapproach.
+  \cite goldberg88newapproach.
 - \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees
-  \ref dinic70algorithm, \ref sleator83dynamic.
+  \cite dinic70algorithm, \cite sleator83dynamic.
 - \ref GoldbergTarjan !Preflow push-relabel algorithm with dynamic trees
-  \ref goldberg88newapproach, \ref sleator83dynamic.
+  \cite goldberg88newapproach, \cite sleator83dynamic.
 
 In most cases the \ref Preflow algorithm provides the
 fastest method for computing a maximum flow. All implementations
@@ -399,20 +399,20 @@
 \brief Algorithms for finding minimum cost flows and circulations.
 
 This group contains the algorithms for finding minimum cost flows and
-circulations \ref amo93networkflows. For more information about this
+circulations \cite amo93networkflows. For more information about this
 problem and its dual solution, see: \ref min_cost_flow
 "Minimum Cost Flow Problem".
 
 LEMON contains several algorithms for this problem.
  - \ref NetworkSimplex Primal Network Simplex algorithm with various
-   pivot strategies \ref dantzig63linearprog, \ref kellyoneill91netsimplex.
+   pivot strategies \cite dantzig63linearprog, \cite kellyoneill91netsimplex.
  - \ref CostScaling Cost Scaling algorithm based on push/augment and
-   relabel operations \ref goldberg90approximation, \ref goldberg97efficient,
-   \ref bunnagel98efficient.
+   relabel operations \cite goldberg90approximation, \cite goldberg97efficient,
+   \cite bunnagel98efficient.
  - \ref CapacityScaling Capacity Scaling algorithm based on the successive
-   shortest path method \ref edmondskarp72theoretical.
+   shortest path method \cite edmondskarp72theoretical.
  - \ref CycleCanceling Cycle-Canceling algorithms, two of which are
-   strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling.
+   strongly polynomial \cite klein67primal, \cite goldberg89cyclecanceling.
 
 In general, \ref NetworkSimplex and \ref CostScaling are the most efficient
 implementations.
@@ -430,7 +430,7 @@
 data are required to be integer).
 
 For more details about these implementations and for a comprehensive 
-experimental study, see the paper \ref KiralyKovacs12MCF.
+experimental study, see the paper \cite KiralyKovacs12MCF.
 It also compares these codes to other publicly available
 minimum cost flow solvers.
 */
@@ -471,7 +471,7 @@
 \brief Algorithms for finding minimum mean cycles.
 
 This group contains the algorithms for finding minimum mean cycles
-\ref amo93networkflows, \ref karp78characterization.
+\cite amo93networkflows, \cite karp78characterization.
 
 The \e minimum \e mean \e cycle \e problem is to find a directed cycle
 of minimum mean length (cost) in a digraph.
@@ -487,11 +487,11 @@
 function.
 
 LEMON contains three algorithms for solving the minimum mean cycle problem:
-- \ref KarpMmc Karp's original algorithm \ref karp78characterization.
+- \ref KarpMmc Karp's original algorithm \cite karp78characterization.
 - \ref HartmannOrlinMmc Hartmann-Orlin's algorithm, which is an improved
-  version of Karp's algorithm \ref hartmann93finding.
+  version of Karp's algorithm \cite hartmann93finding.
 - \ref HowardMmc Howard's policy iteration algorithm
-  \ref dasdan98minmeancycle, \ref dasdan04experimental.
+  \cite dasdan98minmeancycle, \cite dasdan04experimental.
 
 In practice, the \ref HowardMmc "Howard" algorithm turned out to be by far the
 most efficient one, though the best known theoretical bound on its running
@@ -647,8 +647,8 @@
 Various LP solvers could be used in the same manner with this
 high-level interface.
 
-The currently supported solvers are \ref glpk, \ref clp, \ref cbc,
-\ref cplex, \ref soplex.
+The currently supported solvers are \cite glpk, \cite clp, \cite cbc,
+\cite cplex, \cite soplex.
 */
 
 /**