diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index eb154609c..9a1bfe8b6 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -5,13 +5,15 @@ Version: 0.3-0
 Date: 2014-08-23
 Author: Tianqi Chen <tianqi.tchen@gmail.com>, Tong He <hetong007@gmail.com>
 Maintainer: Tong He <hetong007@gmail.com>
-Description: This package is a R wrapper of xgboost, which is short for eXtreme Gradient Boosting.
-  It is an efficient and scalable implementation of gradient boosting framework.
-  The package includes efficient linear model solver and tree learning algorithm.
-  The package can automatically do parallel computation with OpenMP, and it can be
-  more than 10 times faster than existing gradient boosting packages such as gbm.
-  It supports various objective functions, including regression, classification and ranking.
-  The package is made to be extensible, so that user are also allowed to define there own objectives easily.  
+Description: This package is a R wrapper of xgboost, which is short for eXtreme
+    Gradient Boosting. It is an efficient and scalable implementation of
+    gradient boosting framework. The package includes efficient linear model
+    solver and tree learning algorithm. The package can automatically do
+    parallel computation with OpenMP, and it can be more than 10 times faster
+    than existing gradient boosting packages such as gbm. It supports various
+    objective functions, including regression, classification and ranking. The
+    package is made to be extensible, so that user are also allowed to define
+    there own objectives easily.
 License: Apache License (== 2.0) | file LICENSE
 URL: https://github.com/tqchen/xgboost
 BugReports: https://github.com/tqchen/xgboost/issues
diff --git a/R-package/R/xgb.dump.R b/R-package/R/xgb.dump.R
index 2c7813712..dc3f431a2 100644
--- a/R-package/R/xgb.dump.R
+++ b/R-package/R/xgb.dump.R
@@ -5,7 +5,7 @@
 #' @param model the model object.
 #' @param fname the name of the binary file.
 #' @param fmap feature map file representing the type of feature, to make it
-#'        look nice, run demo/demo.R for result and demo/featmap.txt for example
+#'        look nice, run inst/examples/demo.R for result and inst/examples/featmap.txt for example
 #'        Format: https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model
 #'
 #' @examples
diff --git a/R-package/R/xgb.train.R b/R-package/R/xgb.train.R
index ceb87c1cb..99a6dcc2d 100644
--- a/R-package/R/xgb.train.R
+++ b/R-package/R/xgb.train.R
@@ -15,7 +15,7 @@
 #' }
 #'
 #'   See \url{https://github.com/tqchen/xgboost/wiki/Parameters} for 
-#'   further details. See also demo/demo.R for walkthrough example in R.
+#'   further details. See also inst/examples/demo.R for walkthrough example in R.
 #' @param dtrain takes an \code{xgb.DMatrix} as the input.
 #' @param nrounds the max number of iterations
 #' @param watchlist what information should be printed when \code{verbose=1} or
diff --git a/R-package/R/xgboost.R b/R-package/R/xgboost.R
index c6fc99980..6f4633fb8 100644
--- a/R-package/R/xgboost.R
+++ b/R-package/R/xgboost.R
@@ -19,7 +19,7 @@
 #' }
 #'
 #'   See \url{https://github.com/tqchen/xgboost/wiki/Parameters} for 
-#'   further details. See also demo/demo.R for walkthrough example in R.
+#'   further details. See also inst/examples/demo.R for walkthrough example in R.
 #' @param nrounds the max number of iterations
 #' @param verbose If 0, xgboost will stay silent. If 1, xgboost will print 
 #'   information of performance. If 2, xgboost will print information of both
diff --git a/R-package/man/xgb.dump.Rd b/R-package/man/xgb.dump.Rd
index 1e0360b31..69ec13300 100644
--- a/R-package/man/xgb.dump.Rd
+++ b/R-package/man/xgb.dump.Rd
@@ -11,7 +11,7 @@ xgb.dump(model, fname, fmap = "")
 \item{fname}{the name of the binary file.}
 
 \item{fmap}{feature map file representing the type of feature, to make it
-       look nice, run demo/demo.R for result and demo/featmap.txt for example
+       look nice, run inst/examples/demo.R for result and inst/examples/featmap.txt for example
        Format: https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model}
 }
 \description{
diff --git a/R-package/man/xgb.train.Rd b/R-package/man/xgb.train.Rd
index 1f29afa04..aa2778501 100644
--- a/R-package/man/xgb.train.Rd
+++ b/R-package/man/xgb.train.Rd
@@ -20,7 +20,7 @@ xgb.train(params = list(), dtrain, nrounds, watchlist = list(),
 }
 
   See \url{https://github.com/tqchen/xgboost/wiki/Parameters} for
-  further details. See also demo/demo.R for walkthrough example in R.}
+  further details. See also inst/examples/demo.R for walkthrough example in R.}
 
 \item{dtrain}{takes an \code{xgb.DMatrix} as the input.}
 
diff --git a/R-package/man/xgboost.Rd b/R-package/man/xgboost.Rd
index a76ce5b3d..2b6c1a124 100644
--- a/R-package/man/xgboost.Rd
+++ b/R-package/man/xgboost.Rd
@@ -25,7 +25,7 @@ xgboost(data = NULL, label = NULL, params = list(), nrounds,
 }
 
   See \url{https://github.com/tqchen/xgboost/wiki/Parameters} for
-  further details. See also demo/demo.R for walkthrough example in R.}
+  further details. See also inst/examples/demo.R for walkthrough example in R.}
 
 \item{nrounds}{the max number of iterations}