Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Roadmap for Big Model   With the rapid development of deep learning, training Big Models (BMs) for
multiple downstream tasks becomes a popular paradigm. Researchers have achieved
various outcomes in the construction of BMs and the BM application in many
fields. At present, there is a lack of research work that sorts out the overall
progress of BMs and guides the follow-up research. In this paper, we cover not
only the BM technologies themselves but also the prerequisites for BM training
and applications with BMs, dividing the BM review into four parts: Resource,
Models, Key Technologies and Application. We introduce 16 specific BM-related
topics in those four parts, they are Data, Knowledge, Computing System,
Parallel Training System, Language Model, Vision Model, Multi-modal Model,
Theory&Interpretability, Commonsense Reasoning, Reliability&Security,
Governance, Evaluation, Machine Translation, Text Generation, Dialogue and
Protein Research. In each topic, we summarize clearly the current studies and
propose some future research directions. At the end of this paper, we conclude
the further development of BMs in a more general view.

27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th