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How do you suppose an LLM can cite it's sources when it doesn't have one?! It's a language model, not an encyclopedia. The LLM doesn't even get to choose what i
by HarHarVeryFunny 1y ago
How do you suppose an LLM can cite it's sources when it doesn't have one?! It's a language model, not an encyclopedia. The LLM doesn't even get to choose what it outputs - it just gives next word probabilities and one of those is selected AT RANDOM by the sampler.
So, maybe words 1-3 of the LLMs answer are some common turn of speech that was predicted by 1000s of samples, word 4 came from 4chan (a low probability random pick from the sampler), and word 5 was hallucinated. So, what's the "source" for this "fact"?
- bee_rider 1y agoThe fancy online models can produce links for you. They might get the summary wrong, but they’ve got a link, you can follow it and check it out. In this context they are more like conversational search engines. But that’s a pretty decent feature IMO.
- HarHarVeryFunny 1y agoIf the output came from RAG (search) rather than the model itself, then a link is possible, but not if the model just generated the sequence of words by itself. Note too that these models can, and do, make up references. If it predicts a reference is called for, then it'll generate one, and to the LLM it makes no difference if that reference was something actually in the training data or just something statistically plausible it made up.
- ideashower 1y agoThey also search online and return links, though? And, you can steer them when they do that to seek out more "authoritative" sources (e.g. news reports, publications by reputable organizations). If you pay for it, ChatGPT can spend upwards of 5 minutes going out and finding you sources if you ask it to. Those sources can than be separately verified, which is up to the user - of course.
- HarHarVeryFunny 1y agoRight, but now you are not talking about an LLM generating from it's training data - you are talking about an agent that is doing web search, and hopefully not messing it up when it summarizes it.
- yuliyp 1y agoYes, because most of the things that people talk about (ChatGPT, Google SERP AI summaries, etc.) currently use tools in their answers. We're a couple years past the "it just generates output from sampling given a prompt and training" era.
- HarHarVeryFunny 1y agoIt depends - some queries will invoke tools such as search, some won't. A research agent will be using search, but then summarizing and reasoning about the responses to synthesize a response, so then you are back to LLM generation. The net result is that some responses are going to be more reliable (or at least coherently derived from a single search source) than others, but at least to the casual user, maybe to most users, it's never quite clear what the "AI" is doing, and it's right enough, often enough, that they tend to trust it, even though that trust is only justified some of the time.
- bee_rider 1y agoThe models listed in the quote have this capability, though, they must be RAGs or something.
- kordlessagain 1y agoRAG is a horrible term for agentic search. Please stop using it. And, don’t argue with me about terms. It literally stands for retrieval (not store or delete or update) augmented generation. And as generation is implied with LLMs it really just means augmenting with retrieval. But if you think about it the agent could be augmented with stores or updates as well as gets, so that’s why it’s not useful, plus nobody I’ve seen using RAG diagrams EVER show it as an agent tool. It’s always something the system DOES to the agent, not the agent doing it to the data. So yeah, stop using it. Please.
- bee_rider 1y agoWhat if you just read it a Retrieval AGent? It isn’t the conventionally accepted definition but it fits and it might make you happier.
- HarHarVeryFunny 1y agoIf a plain LLM, not an agent, invokes a tool then that can still be considered as RAG. You seem to be thinking of the case where an agent retrieves some data then passes it to an LLM.
- intended 1y agoA year ago there were links to things that didnt exist. Has that changed?
- bee_rider 1y agoI’m sure it is possible to get a model to produce a fake URL, but it seems like ChatGPT has some agentic feature where it actually searches in a search engine or something, and then gives you the URLs that it found.
- anigbrowl 1y agoThis is transparently untrue. Gemini reliably produces links (both inline and at the paragraph level, and most of the time summarizes them correctly. This has been publically available for quite a while now.
- Terr_ 1y agoPerhaps this is a distinction between: 1. "Having sources" because there's something following a logical reasoning process with a knowledge graph. 2. "Having sources" because a hyper-mad-libs hallucinatory engine predicted desirable text which was introduced earlier in the document. We can reduce the chances of humans getting a #2 hallucination that they object-to, but stochastic whack-a-mole doesn't convert it to a #1 mechanism.
- tennysont 1y agoGemini is an LLM with toolcalls (including tools that, approximately, perform a google searchs and read the top results) Not all chatbots are LLMs with toolcalls, and LLMs are perfectly capable of answering without using such toolcalls (and sometimes perform better).
- andai 1y agoA while back I heard "hallucinate and verify" as a good method. The LLM makes up some stuff, then uses RAG to double check it (in Gemini's case, Google, in everyone else's case, a DDoS).
- MengerSponge 1y agoThat's a load bearing "most of the time"
- anigbrowl 1y agoI don't mind in that I'm not expecting perfection; I'm happy to be able to track down a source quicker than I could digging through forum queries or whatever. It's about what I would hope for from a moderately competent intern.
- byzantinegene 1y ago
- deleted 1y ago[deleted]
- afiori 1y agoYou can reductionistically do the same to claim that the mesh of charged gel tubes in our brain is just spasming our muscles when humans type words in a computer. Whether LLM are good or not, liars or not hardly depends on them being implemented on random black boxes algorithms becouse you could say the same of our brains.
- nerdponx 1y agoThe point is that the statement "LLMs should just cite their sources, what's the problem" is nonsensical, and the reason it's nonsense has to do with how LLMs actually work.
- afiori 1y agoCiting sources is not a magic that makes what you say true, it just makes statement more easily falsifiable. LLMs can cite sources as well as any human, that is with a non-trivial error rate. LLMs are shit for a lot of things but the problems are with the quality of the output whether they work by magic, soul-bending, matrix multiplication, or whatever is irrelevant.
- rdedev 1y agoIt's selecting a random word from a probability distribution over words. That distribution is crafted by the LLM. The random sampler is not going to going to choose a word with 1e-6 probability anytime soon. Besides with thinking models, the LLM has the ability to correct itself so it's not like the model is at the mercy of a random number generator
- 1vuio0pswjnm7 1y agoLLMs can fabricate phony citations Like Gemini does