[derefr]

I would argue that an LLM is a perfectly sensible tool for structure-preserving machine translation from another language to English. (Where by "another language", you could also also substitute "very poor/non-fluent English." Though IMHO that's a bit silly, even though it's possible; there's little sense in writing in a language you only half know, when you'd get a less-lossy result from just writing in your native tongue, and then having it translate from that.)

Google Translate et al were never good enough at this task to actually allow people to use the results for anything professional. Previous tools were limited to getting a rough gloss of what words in another language mean.

But LLMs can be used in this way, and are being used in this way; and this is increasingly allowing non-English-fluent academics to publish papers in English-language journals (thus engaging with the English-language academic community), where previously those academics they may have felt "stuck" publishing in what few journals exist for their discipline in their own language.

Would you call the use of LLMs for translation "shoddy" or "irresponsible"? To me, it'd be no more and no less "shoddy" or "irresponsible" than it would be to hire a freelance human translator to translate the paper for you. (In fact, the human translator might be a worse idea, as LLMs are more likely to understand how to translate the specific academic jargon of your discipline than a randomly-selected human translator would be.)

[gus_massa]

Autotranslating technical texts is very hard. After the translation, you muct check that all the technical words were translated correctly, instead of a fancy synonym that does not make sense.

(A friend has an old book translated a long time ago (by a human) from Russian to Spanish. Instead of "complex numbers", the book calls them "complicated numbers". :) )

[QuercusMax]

I remember one time when I had written a bunch of user facing text for an imaging app and was reviewing our French translation. I don't speak French but I was pretty sure "plane" (as in geometry) shouldn't be translated as "avion". And this was human translated!

[jfim]

You'd be surprised how shoddy human translations can be, and it's not necessarily because of the translators themselves.

Typically what happens is that translators are given an Excel sheet with the original text in a column, and the translated text must be put into the next column. Because there's no context, it's not necessarily clear to the translator whether the translation for plane should be avion (airplane) or plan (geometric plane). The translator might not ever see the actual software with their translated text.

[derefr]

The convenient thing in this case (verification of translation of academic papers from the speaker's native language to English) is that the authors of the paper likely already 1. can read English to some degree, and 2. are highly likely to be familiar specifically with the jargon terms of their field in both their own language and in English.

This is because, even in countries with a different primary spoken language, many academic subjects, especially at a graduate level (masters/PhD programs — i.e. when publishing starts to matter), are still taught at universities at least partly in English. The best textbooks are usually written in English (with acceptably-faithful translations of these texts being rarer than you'd think); all the seminal papers one might reference are likely to be in English; etc. For many programs, the ability to read English to some degree is a requirement for attendance.

And yet these same programs are also likely to provide lectures (and TA assistance) in the country's own native language, with the native-language versions of the jargon terms used. And any collaborative work is likely to also occur in the native language. So attendees of such programs end up exposed to both the native-language and English-language terms within their field.

This means that academics in these places often have very little trouble in verifying the fidelity of translation of the jargon in their papers. It's usually all the other stuff in the translation that they aren't sure is correct. But this can be cheaply verified by handing the paper to any fluently-multilingual non-academic and asking them to check the translation, with the instruction to just ignore the jargon terms because they were already verified.

[gus_massa]

> with the native-language versions of the jargon terms used

It depends on the country. Here in Argentina we use a lot of loaned words for technical terms, but I think in Spain they like to translate everything.

[neves]

When reading technical material in my native language, I sometimes need to translate it back to English to fully understand it.

[Davidzheng]

idk I think Gemini 2.5 did a great job at almost all research math papers translating from french to english...

[noooooooph]

To that point I think it's lovely how LLMs democratize science. At ICLR a few years ago I spoke with a few Korean researchers that were delighted that their relative inability to write in English was no being held against them during the review process. I think until then I underestimated how pivotal this technology was in lowering the barrier to entry for the non-English speaking scientific community.

[melagonster]

If they can write a whole draft in their first language, they can easily read the translated English version and correct it. The errors described by gp/op were generated when authors directly required LLM to generate a full paragraph of text. Look at my terrible English; I really have the experience of the full process from draft to English version before :)

[abbassix]

We still do not have a standardized way to represent Machine Learning concepts. For example in vision model, I see lots of papers confused about the "skip connections" and "residual connection" and when they concatenate channels they call them "residual connection" while it shows that they haven't understood why we call them "residual" in the first place. In my humble opinion, each conference, and better be a confederation of conferences, work together to provide a glossary, a technical guideline, and also a special machine translation tool, to correct a non-clear-with-lots-of-grammatical-error-English like mine!

[neves]

I'm surprised by these results. I agree that LLMs are a great tool for offsetting the English-speaking world's advantage. I would have expected non-Anglo-American universities to rank at the top of the list. One of the most valuable features of LLMs from the beginning has been their ability to improve written language.

Why is their use more intense in English-speaking universities?

[neilv]

Good point. There may be a place for LLMs for science writing translation (hopefully not adding nor subtracting anything) when you're not fluent in the language of a venue.

You need a way to validate the correctness of the translation, and to be able to stand behind whatever the translation says. And the translation should be disclosed on the paper.