Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: RocketQAv2: A Joint Training Method for Dense Passage Retrieval and
  Passage Re-ranking   In various natural language processing tasks, passage retrieval and passage
re-ranking are two key procedures in finding and ranking relevant information.
Since both the two procedures contribute to the final performance, it is
important to jointly optimize them in order to achieve mutual improvement. In
this paper, we propose a novel joint training approach for dense passage
retrieval and passage re-ranking. A major contribution is that we introduce the
dynamic listwise distillation, where we design a unified listwise training
approach for both the retriever and the re-ranker. During the dynamic
distillation, the retriever and the re-ranker can be adaptively improved
according to each other's relevance information. We also propose a hybrid data
augmentation strategy to construct diverse training instances for listwise
training approach. Extensive experiments show the effectiveness of our approach
on both MSMARCO and Natural Questions datasets. Our code is available at
https://github.com/PaddlePaddle/RocketQA.

30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas