Active-Prompt
思维链（CoT）方法依赖于一组固定的人工注释范例。问题在于，这些范例可能不是不同任务的最有效示例。为了解决这个问题，Diao 等人（2023）(opens in a new tab)最近提出了一种新的提示方法，称为 Active-Prompt，以适应 LLMs 到不同的任务特定示例提示（用人类设计的 CoT 推理进行注释）。
下面是该方法的说明。第一步是使用或不使用少量 CoT 示例查询 LLM。对一组训练问题生成 k 个可能的答案。基于 k 个答案计算不确定度度量（使用不一致性）。选择最不确定的问题由人类进行注释。然后使用新的注释范例来推断每个问题。
图片来源：Diao等人（2023）
方向性刺激提示
Li 等人，（2023）(opens in a new tab)提出了一种新的提示技术，以更好地指导 LLM 生成所需的摘要。
训练了一个可调节的策略 LM 来生成刺激/提示。越来越多地使用RL来优化 LLM。
下图显示了方向性刺激提示与标准提示的比较。策略 LM 可以很小，并且可以优化以生成指导黑盒冻结 LLM 的提示。
图片来源：Li 等人，（2023）
PAL（程序辅助语言模型）
Gao 等人（2022）(opens in a new tab)提出了一种使用 LLMs 读取自然语言问题并生成程序作为中间推理步骤的方法。被称为程序辅助语言模型（PAL），它与思维链提示不同，因为它不是使用自由形式文本来获得解决方案，而是将解决步骤卸载到类似 Python 解释器的编程运行时中。
图片来源：Gao 等人（2022）(opens in a new tab)
让我们以 LangChain 和 OpenAI GPT-3 为例。我们有兴趣开发一个简单的应用程序，它能够解释所提出的问题，并利用 Python 解释器提供答案。
具体来说，我们有兴趣创建一个功能，允许使用 LLM 回答需要日期理解的问题。我们将为 LLM 提供一个提示，其中包括一些示例，这些示例是从这里(opens in a new tab)采用的。
这是我们需要导入的包：
import openaifrom datetime import datetimefrom dateutil.relativedelta import relativedeltaimport osfrom langchain.llms import OpenAIfrom dotenv import load_dotenv让我们先配置一些环境：
load_dotenv() # API configurationopenai.api_key = os.getenv("OPENAI_API_KEY") # for LangChainos.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")设置模型实例：
llm = OpenAI(model_name='text-davinci-003', temperature=0)设置提示+问题：
question = "Today is 27 February 2023. I was born exactly 25 years ago. What is the date I was born in MM/DD/YYYY?" DATE_UNDERSTANDING_PROMPT = """# Q: 2015 is coming in 36 hours. What is the date one week from today in MM/DD/YYYY?# If 2015 is coming in 36 hours, then today is 36 hours before.today = datetime(2015, 1, 1) - relativedelta(hours=36)# One week from today,one_week_from_today = today + relativedelta(weeks=1)# The answer formatted with %m/%d/%Y isone_week_from_today.strftime('%m/%d/%Y')# Q: The first day of 2019 is a Tuesday, and today is the first Monday of 2019. What is the date today in MM/DD/YYYY?# If the first day of 2019 is a Tuesday, and today is the first Monday of 2019, then today is 6 days later.today = datetime(2019, 1, 1) + relativedelta(days=6)# The answer formatted with %m/%d/%Y istoday.strftime('%m/%d/%Y')# Q: The concert was scheduled to be on 06/01/1943, but was delayed by one day to today. What is the date 10 days ago in MM/DD/YYYY?# If the concert was scheduled to be on 06/01/1943, but was delayed by one day to today, then today is one day later.today = datetime(1943, 6, 1) + relativedelta(days=1)# 10 days ago,ten_days_ago = today - relativedelta(days=10)# The answer formatted with %m/%d/%Y isten_days_ago.strftime('%m/%d/%Y')# Q: It is 4/19/1969 today. What is the date 24 hours later in MM/DD/YYYY?# It is 4/19/1969 today.today = datetime(1969, 4, 19)# 24 hours later,later = today + relativedelta(hours=24)# The answer formatted with %m/%d/%Y istoday.strftime('%m/%d/%Y')# Q: Jane thought today is 3/11/2002, but today is in fact Mar 12, which is 1 day later. What is the date 24 hours later in MM/DD/YYYY?# If Jane thought today is 3/11/2002, but today is in fact Mar 12, then today is 3/12/2002.today = datetime(2002, 3, 12)# 24 hours later,later = today + relativedelta(hours=24)# The answer formatted with %m/%d/%Y islater.strftime('%m/%d/%Y')# Q: Jane was born on the last day of Feburary in 2001. Today is her 16-year-old birthday. What is the date yesterday in MM/DD/YYYY?# If Jane was born on the last day of Feburary in 2001 and today is her 16-year-old birthday, then today is 16 years later.today = datetime(2001, 2, 28) + relativedelta(years=16)# Yesterday,yesterday = today - relativedelta(days=1)# The answer formatted with %m/%d/%Y isyesterday.strftime('%m/%d/%Y')# Q: {question}""".strip() + '\n'llm_out = llm(DATE_UNDERSTANDING_PROMPT.format(question=question))print(llm_out)这将输出以下内容：
# If today is 27 February 2023 and I was born exactly 25 years ago, then I was born 25 years before.today = datetime(2023, 2, 27)# I was born 25 years before,born = today - relativedelta(years=25)# The answer formatted with %m/%d/%Y isborn.strftime('%m/%d/%Y')llm_out 是一段 python 代码，我们可以使用 exec 执行它：
exec(llm_out)print(born)这将输出以下内容：02/27/1998