Research papers discussed in Chapter-2
FINETUNED LANGUAGE MODELS ARE ZERO-SHOT LEARNERS
LANGUAGE MODELS ARE FEW-SHOT LEARNERS
Research papers discussed in Chapter-3
CHAIN-OF-THOUGHT PROMPTING ELICITS REASONING IN LARGE LANGUAGE MODELS
LARGE LANGUAGE MODELS ARE ZERO-SHOT REASONERS
AUTOMATIC CHAIN OF THOUGHT PROMPTING IN LARGE LANGUAGE MODELS
Research papers discussed in Chapter-4
SELF-CONSISTENCY IMPROVES CHAIN OF THOUGHT REASONING IN LANGUAGE MODELS
GENERATED KNOWLEDGE PROMPTING FOR COMMONSENSE REASONING
Research papers discussed in Chapter-11
IN SEARCH FOR LINEAR RELATIONS IN SENTENCE EMBEDDING SPACES
ON THE DIMENSIONALITY OF WORD EMBEDDING