Ani N @Ani_nlp
NLP Ph.D candidate at MIT. Probably reading when I should be coding. Blog at https://t.co/Ne9MXXZxmD anin.dev Cambridge, MA Joined August 2022-
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Ani N retweeted
The people who were warning about tech-induced brain rot 10-20 years ago were right.
The people who were warning about tech-induced brain rot 10-20 years ago were right. https://t.co/DnzvITZiiu
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Ani N retweeted
[1/x] can we scale small, open LMs to o1 level? Using classical probabilistic inference methods, YES! Joint @MIT_CSAIL / @RedHat AI Innovation Team work introduces a particle filtering approach to scaling inference w/o any training! check out …abilistic-inference-scaling.github.io
Ani N retweeted
Verifying LLM outputs is a time-consuming but often necessary endeavor, especially in high-stakes settings. We propose SymGen, a new way to simplify LLM text verification in settings involving structured data! 📄arxiv.org/abs/2311.09188
Ani N retweeted
Our paper has more details on how to make this work. We also made an interactive demo to showcase how SymGen can help you verify LLM text! Paper: arxiv.org/abs/2311.09188 Demo: symgen.github.io w/ @shannonzshen @Ani_nlp Bernhard Gapp @david_sontag @yoonrkim
Ani N retweeted
While classic FL is treated as a distributed optimization problem, recent work (FedPA) showed that FL can be cast as a posterior inference problem. We extend this view by treating FL as a VI problem, which naturally suggests new algorithms. #ICLR2023 arxiv.org/abs/2302.04228
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