Update pipeline tag and add paper link

README.md

@@ -1,5 +1,7 @@
 ---
+library_name: pytorch
 license: mit
+pipeline_tag: other
 tags:
 - relational-deep-learning
 - relational-databases
@@ -13,13 +15,11 @@ tags:
 - few-shot
 - pretraining
 - synthetic-data
-pipeline_tag: tabular-classification
-library_name: pytorch
 ---
 
 # TabWM
 
-TabWM (Tabular World Model) is a relational world model introduced in *Relational Learning as World Modeling*. Given a few observed executions from a relational system, it predicts the structured edits that a new action makes to the database, without updating its parameters. The model is pretrained on WorldRel, a generator of executable relational worlds, and its encoder is initialized from the [RT-PluRel](https://huggingface.co/stanford-star/rt-plurel) Relational Transformer.
+TabWM (Tabular World Model) is a relational world model introduced in [*Relational Learning as World Modeling*](https://huggingface.co/papers/2610.16763). Given a few observed executions from a relational system, it predicts the structured edits that a new action makes to the database, without updating its parameters. The model is pretrained on WorldRel, a generator of executable relational worlds, and its encoder is initialized from the [RT-PluRel](https://huggingface.co/stanford-star/rt-plurel) Relational Transformer.
 
 - **Code:** [github.com/oooranz/TabWM](https://github.com/oooranz/TabWM)
 
@@ -43,4 +43,4 @@ Examples for building behavioral context from WorldRel and running inference are
 
 ## License
 
-MIT. The weights are partly initialized from the PluRel paper checkpoint, whose MIT notice is included in `LICENSE`.
+MIT. The weights are partly initialized from the PluRel paper checkpoint, whose MIT notice is included in `LICENSE`.