Update README.md

README.md

@@ -1,13 +1,18 @@
+Check our SIGIR2021 short paper: https://dl.acm.org/doi/10.1145/3404835.3463048
+
 This checkpoint is a variant of monot5 (T5 pointwise re-ranking model). 
 Specifically, we fuse the "P2Q (i.e. doc2query)" and "Rank (i.e. passage ranking)" to learn the **discriminative** view (Rank) and **geneartive** view (P2Q). 
 
 We found that under the specific **mixing ratio** of these two task, the effectiveness of passage re-ranking improves on par with monot5-3B models.
 Hence, you can try to do both the task with this checkpoint by the following input format:
-- P2Q: Document: <here is a document or a passage> Translate Document to Query:
-- Rank: Query: <here is a query> Document: <here is a document or a passage> Relevant: 
+- P2Q: Document: *\<here is a document or a passage\>* Translate Document to Query:
+- Rank: Query: *\<here is a query\>* Document: *\<here is a document or a passage\>* Relevant: 
+
 which the outputs will be like:
-- P2Q: "<relevant query of the given text>"
-- Rank: "true" or "false"
-(Noted that we usually use the logit values of true/false tokens from T5 reranker as our query-passage relevant scores)
+- P2Q: *\<relevant query of the given text\>*
+- Rank: *true* or *false*
 
-Check our SIGIR2021 short paper: https://dl.acm.org/doi/10.1145/3404835.3463048
+```
+Note that we usually use the logit values of *true*/ *false* token from T5 reranker as our query-passage relevant scores
+Note the above tokens are all case-sensitive.
+```