The Illustrated Transformer
https://jalammar.github.io/illustrated-transformer/
#HackerNews #IllustratedTransformer #NLP #AI #MachineLearning #Visualization
Speech and Language Processing (3rd ed. draft)
https://web.stanford.edu/~jurafsky/slp3/
#HackerNews #SpeechProcessing #LanguageProcessing #NLP #StanfordJurafsky #DraftEdition
Esther Payne :bisexual_flag:
boosted
If you want a specific example of why many researchers in machine learning and natural language processing find the idea that LLMs like ChatGPT or Claude are "intelligent" or "conscious" is laughable, this article describes one:
https://news.mit.edu/2025/shortcoming-makes-llms-less-reliable-1126
#LLM
#ChatGPT
#Claude
#MachineLearning
#NaturalLanguageProcessing
#ML
#AI
#NLP
If you want a specific example of why many researchers in machine learning and natural language processing find the idea that LLMs like ChatGPT or Claude are "intelligent" or "conscious" is laughable, this article describes one:
https://news.mit.edu/2025/shortcoming-makes-llms-less-reliable-1126
#LLM
#ChatGPT
#Claude
#MachineLearning
#NaturalLanguageProcessing
#ML
#AI
#NLP
Andreas Wagner
boosted
We began day 2 of our Large Language Models (LLM) for linguistics research workshop @UniKoeln with a fascinating keynote by Charlotte Pouw on "Interpreting models for speech generation and understanding using methods from #psycholinguistics". Charlotte shared insights from two studies from her #PhD research. Check out the papers: https://aclanthology.org/2025.conll-1.9/ and https://direct.mit.edu/coli/article/50/4/1557/123790. 7/🧵
Oups, I nearly forgot to present our own poster... Luckily, Tiziana Ilie, M.A. student and first author on this project, did a grand job presenting our work on how DeepL deals with pronomial pickups of the hybrid noun "Mädchen". For this study, we used the #OpenSource model OLMo-2-7B to generate our experimental stimuli. Our abstract is here: https://paths.to/m%C3%A4dchen-poster and we will have a preprint out soon so watch this space...
We began day 2 of our Large Language Models (LLM) for linguistics research workshop @UniKoeln with a fascinating keynote by Charlotte Pouw on "Interpreting models for speech generation and understanding using methods from #psycholinguistics". Charlotte shared insights from two studies from her #PhD research. Check out the papers: https://aclanthology.org/2025.conll-1.9/ and https://direct.mit.edu/coli/article/50/4/1557/123790. 7/🧵
Andreas Wagner
boosted
The day featured well-prepared talks, thoughtful questions, and lively exchanges across topics.
A big thank you to Yongxin Huang, our thesis coordinator, for guiding this cohort through the process, and to all supervisors for their continuous support throughout the semester.
We wish all students the best of luck as they finalize their submissions by the end of this month! ✨
(2/2)
The day featured well-prepared talks, thoughtful questions, and lively exchanges across topics.
A big thank you to Yongxin Huang, our thesis coordinator, for guiding this cohort through the process, and to all supervisors for their continuous support throughout the semester.
We wish all students the best of luck as they finalize their submissions by the end of this month! ✨
(2/2)
Andreas Wagner
boosted
Can we trust general-purpose LLMs for rigorous academic work? According to @SarahOberbichler from the #DHlab_IEG, research integrity demands specialized AI models, not general-purpose LLMs when using AI as an analysis tool.
Join her upcoming talk "Argument Mining in News Media: Tailoring Models and Methods for Responsible Application" on Nov 26th at CESR (University of Tours) or online
➡️ https://prima.hypotheses.org/3181
#DigitalHumanities #NLP #ArgumentMining #ResearchIntegrity #AI #LLMs #Histodons #DH
Andreas Wagner
boosted
Promovierende aufgepasst: Ihr seid euch unsicher, ob Topic Modeling das richtige für eure computergestützten Auswertungen ist? Oder doch lieber (nicht) Netzwerkanalyse? Und welche Alternativen gäbe es? Am 17. 11. (16-17:30 Uhr) habt Ihr die Gelegenheit, euch darüber mit unserer Kollegin Cindarella Petz ( @cprog7) im Rahmen des HERMES-Netzwerktreffens (online) auszutauschen.
Infos / Anmeldung: https://hermes-hub.de/aktuelles/events/netzwerktreffen-2025-11-17.html
#DHLab_IEG #HERMES #DigitalHumanities #NLP #TextMining #NetzwerkAnalyse #HNR
Can we trust general-purpose LLMs for rigorous academic work? According to @SarahOberbichler from the #DHlab_IEG, research integrity demands specialized AI models, not general-purpose LLMs when using AI as an analysis tool.
Join her upcoming talk "Argument Mining in News Media: Tailoring Models and Methods for Responsible Application" on Nov 26th at CESR (University of Tours) or online
➡️ https://prima.hypotheses.org/3181
#DigitalHumanities #NLP #ArgumentMining #ResearchIntegrity #AI #LLMs #Histodons #DH
Tiny Diffusion – A character-level text diffusion model from scratch
https://github.com/nathan-barry/tiny-diffusion
#HackerNews #TinyDiffusion #TextModel #DiffusionAI #MachineLearning #NLP
Promovierende aufgepasst: Ihr seid euch unsicher, ob Topic Modeling das richtige für eure computergestützten Auswertungen ist? Oder doch lieber (nicht) Netzwerkanalyse? Und welche Alternativen gäbe es? Am 17. 11. (16-17:30 Uhr) habt Ihr die Gelegenheit, euch darüber mit unserer Kollegin Cindarella Petz ( @cprog7) im Rahmen des HERMES-Netzwerktreffens (online) auszutauschen.
Infos / Anmeldung: https://hermes-hub.de/aktuelles/events/netzwerktreffen-2025-11-17.html
#DHLab_IEG #HERMES #DigitalHumanities #NLP #TextMining #NetzwerkAnalyse #HNR
Word2vec-style vector arithmetic on docs embeddings
https://technicalwriting.dev/embeddings/arithmetic/index.html
#HackerNews #Word2vec-style #vector #arithmetic #on #docs #embeddings #Word2vec #vectorarithmetic #docsembeddings #NLP #MachineLearning
🔗 Learn more:
• Official website → https://sbert.net/
• Original paper → https://aclanthology.org/D19-1410.pdf
• GitHub repository → https://github.com/UKPLab/sentence-transformers
📰 Read the full announcements:
TU Darmstadt Press Release
→ https://www.tu-darmstadt.de/universitaet/aktuelles_meldungen/einzelansicht_528832.de.jsp
Hugging Face Blog Post
→ https://huggingface.co/blog/sentence-transformers-joins-hf
(2/2)
#UKPLab #HuggingFace #SentenceTransformers #NLP #AIresearch #OpenSource 🚀
🚨 #NLP SHARED TASK 🚨
Use Mozilla Common Voice Spontaneous #Speech datasets to train #ASR #SpeechRecognition models that work for conversational speech on 21 under-represented languages.
📆 Dataset release 1 Dec
📆 Submissions 8 Dec
💰 $USD 11k prize pool !!!
Boosts appreciated ❤️
Ulrike Hahn
boosted
🤔 What is #NLP research 𝘳𝘦𝘢𝘭𝘭𝘺 about?
We analyzed 29k+ papers to find out! 📚🔍
📌 Our NLPContributions dataset, from the ACL Anthology, reveals what authors actually contribute—artifacts, insights, and more.
📈 Trends show a swing back towards language & society. Curious where you fit in?
🎁 Tools, data, and analysis await you:
📄 Paper: https://arxiv.org/abs/2409.19505
🌐Project: https://ukplab.github.io/acl25-nlp-contributions/
💻 Code: https://github.com/UKPLab/acl25-nlp-contributions
💾 Data: https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4678
(1/🧵)
🤔 What is #NLP research 𝘳𝘦𝘢𝘭𝘭𝘺 about?
We analyzed 29k+ papers to find out! 📚🔍
📌 Our NLPContributions dataset, from the ACL Anthology, reveals what authors actually contribute—artifacts, insights, and more.
📈 Trends show a swing back towards language & society. Curious where you fit in?
🎁 Tools, data, and analysis await you:
📄 Paper: https://arxiv.org/abs/2409.19505
🌐Project: https://ukplab.github.io/acl25-nlp-contributions/
💻 Code: https://github.com/UKPLab/acl25-nlp-contributions
💾 Data: https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4678
(1/🧵)
Ulrike Hahn
boosted
"Asking scientists to identify a paradigm shift, especially in real time, can be tricky. After all, truly ground-shifting updates in knowledge may take decades to unfold. But you don’t necessarily have to invoke the P-word to acknowledge that one field in particular — natural language processing, or NLP — has changed. A lot.
The goal of natural language processing is right there on the tin: making the unruliness of human language (the “natural” part) tractable by computers (the “processing” part). A blend of engineering and science that dates back to the 1940s, NLP gave Stephen Hawking a voice, Siri a brain and social media companies another way to target us with ads. It was also ground zero for the emergence of large language models — a technology that NLP helped to invent but whose explosive growth and transformative power still managed to take many people in the field entirely by surprise.
To put it another way: In 2019, Quanta reported on a then-groundbreaking NLP system called BERT without once using the phrase “large language model.” A mere five and a half years later, LLMs are everywhere, igniting discovery, disruption and debate in whatever scientific community they touch. But the one they touched first — for better, worse and everything in between — was natural language processing. What did that impact feel like to the people experiencing it firsthand?
Quanta interviewed 19 current and former NLP researchers to tell that story. From experts to students, tenured academics to startup founders, they describe a series of moments — dawning realizations, elated encounters and at least one “existential crisis” — that changed their world. And ours."
https://www.quantamagazine.org/when-chatgpt-broke-an-entire-field-an-oral-history-20250430/
"Asking scientists to identify a paradigm shift, especially in real time, can be tricky. After all, truly ground-shifting updates in knowledge may take decades to unfold. But you don’t necessarily have to invoke the P-word to acknowledge that one field in particular — natural language processing, or NLP — has changed. A lot.
The goal of natural language processing is right there on the tin: making the unruliness of human language (the “natural” part) tractable by computers (the “processing” part). A blend of engineering and science that dates back to the 1940s, NLP gave Stephen Hawking a voice, Siri a brain and social media companies another way to target us with ads. It was also ground zero for the emergence of large language models — a technology that NLP helped to invent but whose explosive growth and transformative power still managed to take many people in the field entirely by surprise.
To put it another way: In 2019, Quanta reported on a then-groundbreaking NLP system called BERT without once using the phrase “large language model.” A mere five and a half years later, LLMs are everywhere, igniting discovery, disruption and debate in whatever scientific community they touch. But the one they touched first — for better, worse and everything in between — was natural language processing. What did that impact feel like to the people experiencing it firsthand?
Quanta interviewed 19 current and former NLP researchers to tell that story. From experts to students, tenured academics to startup founders, they describe a series of moments — dawning realizations, elated encounters and at least one “existential crisis” — that changed their world. And ours."
https://www.quantamagazine.org/when-chatgpt-broke-an-entire-field-an-oral-history-20250430/