What to do if ChatGPT answers are inaccurate, 5 training techniques to make AI more reliable in 2026

ChatGPT What to do if the answer is inaccurate, 5 training techniques to make AI more reliable in 2026

Friends who have used ChatGPT for a while will encounter this embarrassing moment. Ask it a seemingly simple question, and it will seriously make up a piece of information that does not exist. At least it takes a non-existent paper seriously, and at worst it takes wrong code logic and copies it into the project. The problem isn’t that the model itself is stupid, but that we don’t know how to communicate with it. This article compiles 5 truly effective training methods to help you bring ChatGPT’s answer accuracy back to a usable level.

Why ChatGPT is bullshit

The essence of large language models such as ChatGPT is to learn the language probability distribution based on existing corpus, and then predict the next most likely word. It does not have a built-in fact-checking mechanism, so when there is insufficient training data or your question is vague, it will use the sentence that is statistically most similar to the answer to spell out a piece of content that sounds reasonable, but it does not know whether the content actually exists.

This phenomenon is called hallucination in academic circles. Hallucinations are not bugs but side effects of technical principles that can only be alleviated through better questioning and external tools, but cannot be completely eradicated. Once you understand this, you can predict the scenarios in which it is most likely to overturn: historical details, specific figures, cited documents, latest events, and niche knowledge.

The first step is to clearly explain the role and context

Many people ask questions like a search engine, throwing in a few keywords and expecting it to give a complete answer. In this way ChatGPT must guess blindly. A simple way to improve accuracy is to first tell it who you are, what your goals are, who the other party is, and what the constraints are.

For a comparison. The bad question is, help me write a speech. The improved version is that I am the marketing manager of a small home design company. I will give a 10-minute speech at a home furnishing exhibition next week. The goal is to attract retail franchisees. The audience is small and medium-sized bosses with experience in the home furnishing industry. I hope that the tone of the speech is not exaggerated and focuses on the replicability of our products. The amount of information provided by the latter is ten times that of the former, and the accuracy of the manuscript produced is also ten times greater.

The second trick is to paste the original data for it to read.

If you want ChatGPT to answer questions about a certain document, the safest way is not to let it recall it on its own, but to paste the document directly into the conversation and tell it to answer based on the following materials. If you have any guesses outside the materials, please say "I don't know." The professional term for this approach is called in-context learning. A simple understanding is to give it a temporary knowledge base.

ChatGPT now supports uploading PDF and long text, and the context window of the GPT-4 series is enough to hold most white papers or contracts. Claude has its own advantages in long text processing. No matter which tool you use, you cannot skip the step of posting the original text. This is the most effective way to prevent fabrication from the source.

The third trick is to break complex problems into small steps

Let the model solve a complex task in one go, and the error rate will increase exponentially. If you give it a word problem with 5 variables and ask it to calculate the answer in one step, it is likely to make a mistake in one of the steps without knowing it. But if you say that the first step is to list the known conditions clearly, the second step is to set the unknowns, the third step is to list the equations, the fourth step is to solve it, and the fifth step is to verify it, the accuracy rate will be greatly improved.

The scientific name of this practice is chain of thought prompting, English Chain of Thought. Its principle is that when the model generates answers at each step, the previously generated intermediate results will become the context for subsequent reasoning, which is equivalent to leaving a draft for itself. As long as you add a sentence at the end of the question, please think step by step, the effect will be immediate.

The fourth trick is to ask it to output the reasoning process

Just looking at the answers without looking at the process is like accepting homework without correcting it. You have no idea how the students got it right. Let ChatGPT write out its reasoning process, and you can immediately see which step is a reasonable inference and which step is just imagination. If what you see is based on a certain study, and you cannot tell whether this study is real, then this is a high-risk hallucination.

Advanced gameplay is to let it give multiple candidate answers and score them. For example, there are several possible solutions to this question. Please list and evaluate their credibility. Finally, tell me which one you recommend most and why. This way of asking forces it to spread out different hypotheses, and you can pick the most stable one.

The fifth trick is to connect to the Internet when you need to, and change the tools when you need to change tools.

ChatGPT defaults to answering based on training data before the deadline. This deadline will be updated with the version, but it will not reach the present. To ask about any recent news, the latest version number, and the newly released policy, be sure to turn on the search or use the browsing function of the Pro version to search online in real time. Directly turning on the search to ask about the latest events is forcing it to compile.

A more advanced approach is to admit that the question is not suitable for answering and find another tool. For example, when calculating specific numbers, using Wolfram Alpha is much more accurate than GPT. For checking official documents, go to the Docs site of the corresponding product. When doing code debugging, using a dedicated code assistant is more accurate than using a general chat. Treat ChatGPT as a brain instead of an encyclopedia, and its reliability will be much higher.

Corresponding strategies for different tasks

Writing tasks have the lowest risk of hallucinations because they are inherently creative. It should be noted that it is easy to make up the specific names, quotes, and data when writing them. You must check this part yourself.

In the code-based tasks, the short functions are written very stably. When it comes to the new version of the API of the specific library, the old usage will be used. It needs to be corrected after the code is run through.

Academic research tasks require the most caution. All citations must be verified by yourself in the original database. Do not trust the paper title and author combination it gives.

When should you change tools and when should you not hit hard?

If you have practiced the above five tricks for three or five rounds and the answer is still uncertain, then don’t compete with it. This often indicates that there is insufficient training data in this field. The best approach is to change a tool for a specific scenario, or simply check the literature.

Knowing when to give up on AI is also a skill. ChatGPT performs most stably in general knowledge, text rewriting, code snippets, and idea sorting, and requires strict cross-validation in scenarios such as financial analysis, legal opinions, medical diagnosis, and latest events.

FAQ

Can the information fabricated by ChatGPT be identified?

Yes, the usual characteristics are quotes that are too smooth and complete, links that don’t exist, numbers that are too precise but you can’t find the source. Develop the habit of checking references and figures, and you can basically filter out 90% of hallucinations.

Will the accuracy improve after upgrading to Plus?

Yes, the Plus version uses the stronger GPT-4 series model by default, which is much better than the free version in terms of complex reasoning and detailed accuracy, but it cannot eliminate illusions and can only reduce the probability. See the official public page for specific prices.

Is it useful to let it say I don’t know?

it works. Add a sentence to the prompt. If you are not sure, just say you don't know. Don't guess. There is a high probability that the answer will be reduced. But it is not 100% effective, and the model may still misjudge its own degree of certainty.

Is it normal to have different answers to the same question several times?

Normally, this is called the randomness of the output. You can set temperature to 0 during API calls to make the results more stable. It cannot be adjusted in the ChatGPT web version, but asking questions in the same conversation will be more consistent than opening a new conversation.

Are Chinese answers worse than English answers?

Generally speaking, the Chinese corpus is less than that of English, and it is indeed worse in some professional fields. But it has little impact on general tasks. The key to accuracy is the quality of your questions, not the language.