answer
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| question
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B | [
"A. Focused on numeric data processing only",
"B. Strong text encoding/decoding ability and reasoning",
"C. Graph visualization techniques",
"D. Purely academic data structuring"
] | What is a significant contribution of large language models such as GPT4 and LLaMA in the field of natural language processing? |
C | [
"A. Text-only databases",
"B. Graphs visualizing geographical data",
"C. Molecules with descriptions",
"D. Pure numerical graphs"
] | Which of the following scenarios falls into the category of text-paired graphs? |
B | [
"A. For text and graph alignment",
"B. For predicting the final answer",
"C. Only encoding textual information",
"D. Enhancing visualization capabilities in graphs"
] | How are LLMs as predictors utilized according to the context? |
C | [
"A. Predicting complex graph structures",
"B. Generating pure text responses",
"C. Obtaining feature vectors from the inputs",
"D. Aligning graphs with non-textual data"
] | What role does the 'LLM as Encoder' play in the context of graphs and LLMs? |
C | [
"A. Natural language processing",
"B. Graph representation learning",
"C. Numeric data processing",
"D. Text encoding/decoding"
] | In which area are LLMs NOT typically used, based on the document? |
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