F ANALYSIS OF DOMAIN KNOWLEDGE AND PROMPTING ABILITY

Table 12: Fine-tuning performance on the domain-specific tasks of general large language model
(General LLM), the model trained on domain-specific raw corpora (Raw Text) and the model
trained on the reading comprehension texts constructed based on the raw corpora (Read. Compre.).

PubMedQA ChemProt MQP RCT UMSLE AVERAGE

BioMed.
General LLM
Raw Text
Read. Compre.

Finance
General LLM
Raw Text
Read. Compre.

75.4
76.2
76.0

58.1
56.2
57.2

64.6
64.8
65.4

55.4
65.6
87.9

87.0
87.0
87.5

38.5
39.0
41.0

81.9
83.3
88.6

86.4
87.9
83.1

95.7
95.8
96.1

77.5
81.3
82.5

ConvFinQA FPB FiQA SA Headline NER AVERAGE

Law

General LLM
Raw Text
Read. Compre.

SCOTUS

CaseHOLD

mic-F1 mac-F1 mic-F1 mac-F1
31.7
36.7
40.0

35.3
35.4
35.5

35.3
35.4
35.5

14.0
26.0
26.0

93.8
93.7
94.2

UNFAIR-ToS AVERAGE

64.2
66.5
71.5

79.9
80.9
81.5

42.0
45.4
46.2

21
ADAPTINGLARGELANGUAGEMODELSVIA READINGCOMPREHENSION