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This take us overly cynical in this case—the original and primary use case for LLMs is to model languages in a comprehensive way. It's literally in the name. H

This take us overly cynical in this case—the original and primary use case for LLMs is to model languages in a comprehensive way. It's literally in the name. Hallucinations rarely make up invalid grammar or invent non-existent words, what we're concerned about is facts, which isn't relevant at all when the goal is language preservation.

userbinator 2y ago
Depending on how powerful the language modeling is, I suspect it could lead to an LLM which will confidently and convincingly tell you how to say things like "floppy disk" and "SSD" in every extinct language and even those that went extinct long before computers ever existed, which is... interesting, but not exactly truth. I've seen LLMs hallucinate nonexistent things in programming languages. It's hard to believe it won't do the same to human ones.
- idunnoman1222 2y ago
  …Hallucinates a non-existent setting that could easily be added in a PR and merged tomorrow
- lolinder 2y ago
  Importantly, the hallucinating non-existent things in programming languages is still stringing together valid English words to make something that looks like it ought to be a correct concept. It doesn't construct new words from scratch. If a language model were asked what the word for "floppy disk" was in an extinct language and it invented a decent circumlocution, I don't think that would be a bad thing. People who are just engaging with the model as a way of connecting with their cultural heritage won't mind much if there is some creative application, and scholars are going to be aware of the limitations. Again, the misapplication of language models as databases is why hallucinations are a problem. This use case isn't treating the model as a database, it's treating the model as a model, so the consequences for hallucination are much smaller to the point of irrelevance.
  - lyu07282 2y ago
    I also don't think it was ever much of a problem for machine translation to begin with. Also modern conversational systems are already addressing the problem (with things like contrastive/counterfactual fine-tuning and RAG/in-context learning) and will just tell you if it doesn't know something instead of hallucinating. But I'm pretty sure op doesn't know the difference between a language model and conversational model anyway, its just the generic "anti-LLM" opinion without much substance.
- ahoef 2y ago
  Isn't this something humans would also do if there were native speakers left to speak the language?
  - Lanolderen 2y ago
    It's common in non-dead languages. If your language is smaller you're bound to have a lot of "foreign words" in it. To this day I find it funny how my native language teachers would start to speak with tons of english and french words when they wanted to "showcase the complexity/beauty of our native language"/appear smart. An LLM should do fine with that since it's usually the foreign word spelled in a way that makes sense in that language. I'm more curious about the inverse though. It's sometimes quite difficult to explain the meaning of a word in a language that does not have an equivalent, be it because it has a ton of different meanings or because it's some very specific action/object.
- diggan 2y ago
  How would terms like "floppy disk" and "SSD" even appear in the target language if those terms weren't around when the speakers of the language was alive? Or you're thinking a multi-language LLM that tries to automatically translate between terms it didn't actually see in the source/target language during training?
cess11 2y ago
They're kind of bad at pretty much all languages, except simpler forms of english and Python. The tonality in the big LLM:s tends to be distinctly inhuman as well. I suspect it'll be hard to find more material in some obscure, dying language than there is of either of those in the common training sets.
- ahoef 2y ago
  What language have you tried that they're bad at? I've tried a bunch of European languages and they are all perfect (or perfect enough for me to never know otherwise)
  - cess11 2y ago
    Swedish, german, spaniard spanish, french and luxembourgish french. Sometimes they do a decent translation, too often they trip up on grammar, vocabulary or just assuming that a string of bytes means the same thing always. I find they work best in extremely formal settings, like documents produced by governments and lawyers.
- lolinder 2y ago
  What is "they"? Are you saying transformer architecture somehow is biased towards English? Or are you saying that existing LLMs have that bias? The only way this project is going to make sense will be to train it fresh on text in the language to be preserved, in order to avoid accidentally corrupting your model with English. If it's trained fresh on only target language content, I'm not sure how we can possibly generalize from the whole-internet models that you're familiar with.
  - cess11 2y ago
    I don't really care about the minutiae of the technical implementations, I'm talking from the experience of pushing text into LLM:s locally and remote, and getting translation in some direction or other back. To me it doesn't make sense. It seems like an awful way to store information about a fringe language, but I'm certainly not an expert.

userbinator 2y ago

Depending on how powerful the language modeling is, I suspect it could lead to an LLM which will confidently and convincingly tell you how to say things like "floppy disk" and "SSD" in every extinct language and even those that went extinct long before computers ever existed, which is... interesting, but not exactly truth. I've seen LLMs hallucinate nonexistent things in programming languages. It's hard to believe it won't do the same to human ones.

idunnoman1222 2y ago
…Hallucinates a non-existent setting that could easily be added in a PR and merged tomorrow
lolinder 2y ago
Importantly, the hallucinating non-existent things in programming languages is still stringing together valid English words to make something that looks like it ought to be a correct concept. It doesn't construct new words from scratch. If a language model were asked what the word for "floppy disk" was in an extinct language and it invented a decent circumlocution, I don't think that would be a bad thing. People who are just engaging with the model as a way of connecting with their cultural heritage won't mind much if there is some creative application, and scholars are going to be aware of the limitations. Again, the misapplication of language models as databases is why hallucinations are a problem. This use case isn't treating the model as a database, it's treating the model as a model, so the consequences for hallucination are much smaller to the point of irrelevance.
- lyu07282 2y ago
  I also don't think it was ever much of a problem for machine translation to begin with. Also modern conversational systems are already addressing the problem (with things like contrastive/counterfactual fine-tuning and RAG/in-context learning) and will just tell you if it doesn't know something instead of hallucinating. But I'm pretty sure op doesn't know the difference between a language model and conversational model anyway, its just the generic "anti-LLM" opinion without much substance.
ahoef 2y ago
Isn't this something humans would also do if there were native speakers left to speak the language?
- Lanolderen 2y ago
  It's common in non-dead languages. If your language is smaller you're bound to have a lot of "foreign words" in it. To this day I find it funny how my native language teachers would start to speak with tons of english and french words when they wanted to "showcase the complexity/beauty of our native language"/appear smart. An LLM should do fine with that since it's usually the foreign word spelled in a way that makes sense in that language. I'm more curious about the inverse though. It's sometimes quite difficult to explain the meaning of a word in a language that does not have an equivalent, be it because it has a ton of different meanings or because it's some very specific action/object.
diggan 2y ago
How would terms like "floppy disk" and "SSD" even appear in the target language if those terms weren't around when the speakers of the language was alive? Or you're thinking a multi-language LLM that tries to automatically translate between terms it didn't actually see in the source/target language during training?

cess11 2y ago

They're kind of bad at pretty much all languages, except simpler forms of english and Python. The tonality in the big LLM:s tends to be distinctly inhuman as well. I suspect it'll be hard to find more material in some obscure, dying language than there is of either of those in the common training sets.

ahoef 2y ago
What language have you tried that they're bad at? I've tried a bunch of European languages and they are all perfect (or perfect enough for me to never know otherwise)
- cess11 2y ago
  Swedish, german, spaniard spanish, french and luxembourgish french. Sometimes they do a decent translation, too often they trip up on grammar, vocabulary or just assuming that a string of bytes means the same thing always. I find they work best in extremely formal settings, like documents produced by governments and lawyers.
lolinder 2y ago
What is "they"? Are you saying transformer architecture somehow is biased towards English? Or are you saying that existing LLMs have that bias? The only way this project is going to make sense will be to train it fresh on text in the language to be preserved, in order to avoid accidentally corrupting your model with English. If it's trained fresh on only target language content, I'm not sure how we can possibly generalize from the whole-internet models that you're familiar with.
- cess11 2y ago
  I don't really care about the minutiae of the technical implementations, I'm talking from the experience of pushing text into LLM:s locally and remote, and getting translation in some direction or other back. To me it doesn't make sense. It seems like an awful way to store information about a fringe language, but I'm certainly not an expert.