#textgeneration — Public Fediverse posts

Natural Language Autoencoders: Turning Claude's Thoughts into Text

https://www.anthropic.com/research/natural-language-autoencoders

#HackerNews #NaturalLanguageProcessing #Autoencoders #Claude #AIResearch #TextGeneration

AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation

https://arxiv.org/abs/2305.09515

#HackerNews #ARDiffusion #TextGeneration #AutoRegressive #AIResearch #MachineLearning

We currently have two fully-funded open PhD positions in our group with a focus on #NLProc, #InformationExtraction and #TextGeneration. I can really recommend both the group as well as Philipp Cimiano as a supervisor, so take this opportunity!

NLP/Text Generation
EN: https://uni-bielefeld.hr4you.org/job/view/4054
DE: https://uni-bielefeld.hr4you.org/job/view/4053

NLP/Information Extraction
EN: https://uni-bielefeld.hr4you.org/job/view/4059
DE: https://uni-bielefeld.hr4you.org/job/view/4057

If you have any questions, do not hesitate to contact me or Philipp directly!

#HowToThing #030 — Procedural, rule-based & stochastic text generation using a custom DSL, parse grammar (via https://thi.ng/parse) and abstract syntax tree transformation (via https://thi.ng/defmulti).

Since it's #NaNoWriMo & #NaNoGenMo [1], I'm closing out this first season of 30 #HowToThing's with a related topic & maybe someone even finds it useful/interesting... 😉🤷‍♂️

This example is in principle inspired by @galaxykate's oldie & goodie #Tracery, but is using a super simple custom text format instead of JSON to define variables and template text. Variables are expanded recursively and I've also added features like dynamic, indirect pointer-like variable lookups to derive variables based on current values (useful for conditionals & context-specific expansions), hidden assignments, chainable modifiers... I've included 5 different "story" templates (incl. comments) showing various features. Just press "regenerate" to create new random variations...

Similar to the previous #HowToThing, I'm hoping this example also shows that approaching use cases like this via small domain-specific languages with proper grammar rules, does not require much ceremony and is often more amenable to change during prototyping (and later also more maintainable!) than just regex bashing approaches...

The parser grammar itself is explained in the https://thi.ng/parse readme. As usual, the grammar was created/prototyped with the Parser Playground[2], which we developed from scratch during the first thi.ng livestream[3] (2.5h video)...

Demo (example project #145):
https://demo.thi.ng/umbrella/procedural-text/

Source code:
https://github.com/thi-ng/umbrella/tree/develop/examples/procedural-text/src

If you have any questions about this topic or the packages used here, please reply in thread or use the discussion forum (or issue tracker):

https://github.com/thi-ng/umbrella/discussions

[1] https://github.com/NaNoGenMo/2023/
[2] https://demo.thi.ng/umbrella/parse-playground/
[3] https://www.youtube.com/watch?v=mXp92s_VP40

#ThingUmbrella #NaNoWriMo2023 #NaNoGenMo2023 #ProcGen #Generative #TextGeneration #Ngram #TypeScript #JavaScript #Tutorial

What are large language models, and how to deploy them? - Explore the world of large language models and AI wonders designe... - https://cointelegraph.com/news/large-language-models #largelanguagemodels #textgeneration #aideployment #chatbots