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Chain-of-Thought

106 articles · Page 2 of 2
ByteFE
ByteFE
Jun 15, 2023 · Artificial Intelligence

Effective Prompt Engineering: Techniques, Prompt Injection Prevention, Hallucination Mitigation, and Advanced Prompting Strategies

This article explains how to craft efficient prompts by combining clear instructions and questions, discusses prompt injection risks and mitigation with delimiters, addresses hallucinations, and introduces zero‑shot, few‑shot, and chain‑of‑thought prompting techniques for large language models.

Chain-of-ThoughtFew-shotHallucination
0 likes · 16 min read
Effective Prompt Engineering: Techniques, Prompt Injection Prevention, Hallucination Mitigation, and Advanced Prompting Strategies
Architect
Architect
Apr 19, 2023 · Artificial Intelligence

Emergence in Large Language Models: Phenomena, Explanations, and Implications

This article reviews the emergence phenomena observed in large language models, explains how model scale, in‑context learning and chain‑of‑thought prompting contribute to sudden performance gains, discusses small‑model alternatives, and explores the relationship between emergence and the training‑time Grokking effect.

AI researchChain-of-ThoughtIn-Context Learning
0 likes · 13 min read
Emergence in Large Language Models: Phenomena, Explanations, and Implications
DataFunSummit
DataFunSummit
Mar 19, 2023 · Artificial Intelligence

Complex Question Answering Evaluation of ChatGPT

This paper presents a large‑scale evaluation of ChatGPT on knowledge‑base complex question answering, introducing a feature‑driven multi‑label annotation framework and CheckList‑based functional, robustness, and controllability tests, and comparing its performance with other LLMs across multiple English and multilingual datasets.

Chain-of-ThoughtChatGPTComplex QA
0 likes · 25 min read
Complex Question Answering Evaluation of ChatGPT
DataFunTalk
DataFunTalk
Feb 21, 2023 · Artificial Intelligence

Analysis of Large Language Models: Capabilities, Training Methods, and Limitations – Summary of Prof. Qiu Xipeng’s Lecture

Prof. Qiu Xipeng’s lecture provides a comprehensive overview of large language models—from their historical development and architectural foundations to key technologies such as in‑context learning, chain‑of‑thought, and natural‑instruction learning, as well as RLHF training, capability evaluation, and current limitations of ChatGPT.

Chain-of-ThoughtChatGPTIn-Context Learning
0 likes · 15 min read
Analysis of Large Language Models: Capabilities, Training Methods, and Limitations – Summary of Prof. Qiu Xipeng’s Lecture