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I entered the #ComputationalLinguistics field in 2018 by enrolling for a Bachelor's degree.
Since then, a lot has changed. Almost all the things we learned about, programmed in practice and did research on are now nearly irrelevant in our day-to-day.
Everything is #LLMs now. Every paper, every course, every student project.
And the newly enrolled students changed, too. They're no longer language nerds, they're #AI bros.
I miss #CompLing before ChatGPT.
@lianna LLMs really flooded the zone with shit, but even in 2018, things felt in decline.
One thing frustrating was everyone using BERT as a baseline, then comparing with their model, then calling it a day.
Was BERT actually good at this task? What if I did something simple, like a majority class baseline, or a tf-idf vector model? These kind of contextualizing baselines were abandoned, and it’s only gotten worse since.
@thedansimonson I think part of the reason is the constant push to publish.
No wonder people are taking shortcuts just to get something out.
If my job and therefore my livelihood depended on it, of course I would choose the "easy way" and just do a throwaway "we tried a new hyperparameter and here's how it compares to <insert popular model>" thing too.