[HN Gopher] When do you need chain-of-thought prompting for Chat...
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When do you need chain-of-thought prompting for ChatGPT?
Author : belter
Score : 84 points
Date : 2023-04-09 14:30 UTC (8 hours ago)
(HTM) web link (arxiv.org)
(TXT) w3m dump (arxiv.org)
| siavosh wrote:
| Is COT considered a deep area of engineering/research or is it
| considered as simply a temporary hack that will be obsolete in
| the near or medium term?
| [deleted]
| travisjungroth wrote:
| I don't know of a consensus for it to be "considered" one way
| or another. I think explicitly asking for COT is temporary, and
| it will move to a layer that's encapsulated from most users. It
| will persist there as long as long as the language layer is
| doing the "thinking". If the language layer is completely
| offloading that and just translating, it won't be needed.
|
| I've been explaining it to people as "if ChatGPT can think, it
| can only think out loud". Because of the way LLMs were trained,
| nudging it to do this will continue to be valuable.
|
| Most writing about anything difficult is product, not process.
| Articles get drafts before being published. People think about
| answers before writing them down. How to Solve It does a great
| job explaining this about math problems. The steps to the proof
| are not the steps to creating the proof.
|
| So when you go to solve a problem by mimicking the solutions to
| problems, something is missing. People will either need to
| train LLMs to do it, or continue to ask for it in prompts.
| Ozzie_osman wrote:
| Despite the fancy name (Chain Of Thought) and multiple arxiv
| papers, I'd definitely consider it a temporary hack that the
| models will overcome as they get more powerful and as they are
| better-trained to avoid hallucination. From this paper, it
| looks like ChatGPT may have already overcome it for some types
| of questions.
|
| What may be here to stay might be more task-specific prompting
| to break a problem down. For example, a variation might be
| "Let's think step by step, making sure we do or consider X
| before we do Y".
|
| By way of analogy, when my toddler was really young, if he
| couldn't figure something out, I'd ask him to break it down
| into steps (very similar to general Cot prompting). Now, he
| rarely needs that, but still needs more occasional, task-
| specific "prompting", eg "Let's think about the weather, and
| what we're going to be doing, before deciding what to wear".
| wiradikusuma wrote:
| Does anyone know a good tutorial for producing good prompts? I
| forgot the document name, but last time there was a "bible" for
| producing good results from text-to-image.
| splatzone wrote:
| Are you referring to the DALLE-2 prompt book?
| https://dallery.gallery/wp-content/uploads/2022/07/The-DALL%...
| belter wrote:
| "...Chain-of-Thought (CoT) prompting can effectively elicit
| complex multi-step reasoning from Large Language Models~(LLMs).
| For example, by simply adding CoT instruction ``Let's think step-
| by-step'' to each input query of MultiArith dataset, GPT-3's
| accuracy can be improved from 17.7\% to 78.7\%. However, it is
| not clear whether CoT is still effective on more recent
| instruction finetuned (IFT) LLMs such as ChatGPT. Surprisingly,
| on ChatGPT, CoT is no longer effective for certain tasks such as
| arithmetic reasoning while still keeping effective on other
| reasoning tasks. Moreover, on the former tasks, ChatGPT usually
| achieves the best performance and can generate CoT even without
| being instructed to do so...
|
| ...Hence, it is plausible that ChatGPT has already been trained
| on these tasks with CoT and thus memorized the instruction so it
| implicitly follows such an instruction when applied to the same
| queries, even without CoT. Our analysis reflects a potential risk
| of overfitting/bias toward instructions introduced in IFT, which
| becomes more common in training LLMs..."
| amrb wrote:
| I found to very difficult to set goals with gpt-turbo, maybe
| gpt4 will be a good test when I get access.
|
| Also I'm thinking would be interesting to train a LoRa, using
| synthetic prompts.
| nerdponx wrote:
| It's really weird to me that we now have research papers
| dedicated to exploring the emergent behavior of systems that
| other people built, but where the researchers can only
| speculate about what the builders actually did to build the
| thing. "Open" AI indeed.
| rmbyrro wrote:
| I think the "Open" in OpenAI is about open access, not open
| source. I'm really glad they are "democratic" in releasing
| their products. I'd hate if I had to go through a "Talk to
| our salespeople" form ik order to use them.
| colordrops wrote:
| No, that's not what they meant. Read the history of its
| founding. They changed their charter after it was founded.
| monsieurbanana wrote:
| With that definition every single big software company is
| open. Microsoft the most open of all, they don't care if
| you pirate Windows as it brings them more market share.
| throwawayapples wrote:
| Then they wouldn't be nearly as good. You're training GPT
| for them for free (or even paying them for the privilege.)
| jacquesm wrote:
| It might also be post/pre processing.
| boringuser2 wrote:
| Any type of additional explanation that isn't strictly necessary
| is currently painful on the GPT-4 plan.
| cubefox wrote:
| Bing Chat (Sydney) has 20 turns per conversation and 200 turns
| per day, free.
| raylad wrote:
| Which is the same as the paid ChatGPT plan when using GPT-4:
| 25 turns every 3 hours.
|
| Bing's free one is better in that sense in that you can use
| all 200 over a shorter timespan.
| chrispogeek wrote:
| I think COT would still be useful for guiding the LLM to
| customized context. Most of these examples refer to vanilla
| arithmetic/logic reasoning COT.
| leobg wrote:
| I think the ideas is that the LLM cannot think internally. It's
| output _is_ its thinking process. Especially with an auto
| regressive architecture like GPT, where each output token becomes
| part of the input.
|
| I imagine it like handing the LLM a piece of scratch paper.
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