AI“Beyond Repeated Sampling” targets more efficient LLM reasoning
KempeLab says its new paper explores using learned concepts to make large language model reasoning more efficient at test time.
TLDR
KempeLab announced “Beyond Repeated Sampling,” describing learned concepts as a way to make large language model reasoning more efficient at test time—when a model generates answers.
“Beyond Repeated Sampling” targets more efficient LLM reasoning
KempeLab says its new paper explores using learned concepts to make large language model reasoning more efficient at test time.