Our paper - "GCM: A Toolkit for Generating Synthetic Code-mixed Text" has been accepted at the 16th Conference of European Chapter of the Association for Computational Linguistics @eaclmeeting in the demo paper track.
@Im_IrushiK I am guessing here but AWS like IaaS would be existing then. And Perl and PHP has been used for making websites and servers even Facebook started with PHP. Why do you need Docker or Kubernetes when you can build your own IaaS? And migrations/deployment can be done manually.
LLMs are fluent today—but only by conquering hallucinations can they become truly trustworthy.
In my latest blog, I explore why this challenge matters, the most promising solutions, and what’s next for LLMs.
https://t.co/GuHZQHoTBT
#AI#LLM#NLP#TrustworthyAI#ChatGPT
Huge shout-out to my incredible collaborators Alex Murphy, Aden Haussmann, Ping Nie, Guifu Liu, @aryopg , & @PMinervini at @EdinburghNLP and @EdinburghUni! 🙌
This is a big step toward grounded, hallucination-free LLMs!
Check out our research & let’s discuss!
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🚀 New ArXiv paper alert!
By combining agentic frameworks (ReAct) with smart decoders (DeCoRe, DoLa, CAD), we boost factual accuracy in complex reasoning tasks —reducing those annoying hallucinations! 🔥
🔗 Paper: https://t.co/4spoFrSOXH
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Probably not what you want to hear but docs 😅. Actual real life examples. Better and more comprehensive kwarg docs. More helpful links to actual code not just wrapper of wrapper of wrapper code. Example code of larger apps showing best practices (style of torch titan, nanoGPT or etc). Helpful historical context if any, possibly links to useful issues. In process of my zero to hero videos I think I’ve come by ~10 examples of bad, incomplete, unhelpful or misleading docs where you just kinda have to know somehow.
I’m thrilled to share that I’ve graduated with Distinction from the M.S. Speech & Language Processing (NLP & AI) program at The University of Edinburgh @EdinburghNLP (1/n)