Nov 14, 2023 · A novel semi-structured prompting approach that seamlessly integrates the model's parametric memory with unstructured knowledge from text documents and ...
Our work addresses the research question of how to efficiently integrate the three primary knowledge sources during inference time: parametric memory of LLMs, ...
Jun 16, 2024 · An important open question in the use of large language models for knowledge-intensive tasks is how to effectively integrate knowledge from.
Semi-Structured Chain-of-Thought: Integrating Multiple Sources of. Knowledge for Improved Language Model Reasoning. Anonymous ACL submission. Abstract. An ...
Nov 13, 2023 · The Semi-CoT approach boosts LLM reasoning by blending the model's internal knowledge, external databases, and unstructured data.
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Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning. Su, X., Le, T., Bethard, S., & Howard, P.
Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning. X Su, T Le, S Bethard, P Howard. arXiv ...
Jun 12, 2024 · Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning https://t.co/gN1YML7AIu.
We introduce NeuroComparatives, a novel framework for comparative knowledge distillation overgenerated from language models such as GPT-variants and LLaMA.
This repository contains the resources for ACL 2024 paper Navigate through Enigmatic Labyrinth, A Survey of Chain of Thought Reasoning: Advances, Frontiers and ...