diff --git a/Colada/WordClass.hs b/Colada/WordClass.hs
--- a/Colada/WordClass.hs
+++ b/Colada/WordClass.hs
@@ -180,14 +180,20 @@
                          (get topicNum opts)
                          (get alphasum opts)
                          (get beta opts)
-                         (get exponent opts)
-        Fold.forM_ bs $ \b -> do
+        Fold.forM_ bs $ \b -> do 
+          _ <- ST.stToIO . LDA.run m (get passes opts) . Fold.msum $ b 
+          when (get progressive opts) $ do
+            Fold.forM_ b $ \sent -> do
+              ls <- ST.stToIO $ V.mapM (interpWordClasses m (get lambda opts)) sent
+              f ls
+ {-         
           Fold.forM_ [1..get passes opts] $ \i -> do
             Fold.forM_ b $ \sent -> do
               _ <- ST.stToIO $ LDA.pass 1 m sent
               when (get progressive opts && i == get passes opts) $ do
                 ls <- ST.stToIO $ V.mapM (interpWordClasses m (get lambda opts)) sent
                 f ls
+-}
         ST.stToIO $ LDA.finalize m    
   lda <- sampler
   return (WordClass lda atomTabD atomTabW opts)
@@ -219,7 +225,8 @@
   where doc (d, ws) = do
           da  <- Symbols.toAtomA . compress $ d
           was <- mapM (Symbols.toAtomB . compress) ws
-          return (da, U.fromList $ zip was (repeat Nothing))
+          --return (da, U.fromList $ zip was (repeat Nothing))
+          return (da, U.fromList was)
 
 -- | @summary m@ returns a textual summary of word classes found in
 -- model @m@
@@ -259,8 +266,9 @@
 -- | @interpWordClasses m lambda doc@ gives the class probabilities for
 -- word type in context @doc@ according to evolving model @m@. It
 -- interpolates the prior word type probability with the
--- context-conditioned probabilities using alpha: 
--- P(d,w) = lambda * P(z|d) + (1-lambda) * P(z|d,w)
+-- context-conditioned probabilities using lambda: 
+-- P(d,w) = lambda * P(z|d) + (1-lambda) * P(z|d,w).
+-- This function does not mutate any weights of the model.
 interpWordClasses ::    LDA.LDA s
                      -> Double 
                      -> LDA.Doc 
@@ -296,7 +304,7 @@
                                       (L.get wordTypeTable m) 
                                       (L.get featureTable m) 
   where dectx doc@(d, _) = if noctx 
-                           then (d, U.singleton (-1,Nothing)) --FIXME: ugly hack
+                           then (d, U.singleton (-1)) --FIXME: ugly hack
                            else doc
         label' = do
           let fm = L.get ldaModel m
@@ -319,7 +327,7 @@
                     . V.toList 
                     $ s'
           mapM (V.mapM fromAtom) ws
-        docToWs = U.map fst . snd
+        docToWs = snd
         fromAtom (n,w) = do w' <- Symbols.fromAtomA w
                             return (n, decompress w')
 
diff --git a/colada.cabal b/colada.cabal
--- a/colada.cabal
+++ b/colada.cabal
@@ -1,5 +1,5 @@
 Name:                colada
-Version:             0.7.0.0
+Version:             0.8.0.0
 Synopsis:            Colada implements incremental word class class induction 
                      using online LDA
 Description:  Colada implements incremental word class class induction using 
@@ -27,7 +27,7 @@
                , cmdargs >= 0.9
                , bytestring >= 0.9
                , mtl >= 2.0
-               , swift-lda >= 0.4 && <= 0.5
+               , swift-lda >= 0.7 && < 0.8
   Exposed-modules:  Colada.WordClass
                   , NLP.CoNLL
   Other-modules: Colada.Features
@@ -50,7 +50,7 @@
                , cmdargs >= 0.9
                , bytestring >= 0.9
                , mtl >= 2.0
-               , swift-lda >= 0.4 && <= 0.5
+               , swift-lda >= 0.7 && < 0.8
   Other-modules: Colada.WordClass
                , Colada.Features
                , NLP.CoNLL