Juri Opitz
@nlopitz.bsky.social
Researcher at University of Zurich https://www.juriopitz.com/
NLP relies on Linguistics & that's capital RELIES! It encapsulates 6 major facets where linguistics contributes to NLP: Resources, Evaluation, Low-resource settings, Interpretability, Explanation, & the Study of language. Read it at doi.org/10.1162/coli... @nlopitz.bsky.social @complingy.bsky.social
LLMs can't parse (yet) --- New Blog Post! juriopitz.com/2025/08/26/l...
LLMs can’t parse (yet)
LLMs can’t parse (yet)
juriopitz.com
Happy to share that my amazing co-authors will be presenting some of our recent work at ACL 2025 next week! If you’re interested in these topics please feel free to drop by and connect. (Paper links in comments 👇)
I might be able to hire a postdoc for this fall in computational linguistics at UT Austin. Topics in the general LLM + cognitive space (particularly reasoning, chain of thought, LLMs + code) and LLM + linguistic space. If this could be of interest, feel free to get in touch!
Applications are now open for the graduate programme in "Linguistic Computing" at Università Cattolica del Sacro Cuore! #Milan #NLProc #artificalintelligence www.unicatt.it/en/programme...
Our survey highlights the enduring influence of linguistics on #NLProc. We emphasize 6 facets: Resources, Evaluation, Low-resource settings, Interpretability, Explanation, and the Study of language.
Juri Opitz@nlopitz.bsky.social · 2y agoHappy to share that our paper, "Natural Language Processing RELIES on Linguistics," will appear in Computational Linguistics! Preprint: arxiv.org/abs/2405.05966
Happy to share that our paper, "Natural Language Processing RELIES on Linguistics," will appear in Computational Linguistics! Preprint: arxiv.org/abs/2405.05966
Interpretable Text Embeddings and Text Similarity Explanation: A Primer Provides a comprehensive overview of methods for explaining text embeddings and similarity scores, covering space shaping, set-based, and attribution approaches. 📝 arxiv.org/abs/2502.14862
Interpretable Text Embeddings and Text Similarity Explanation: A Primer
Text embeddings and text embedding models are a backbone of many AI and NLP systems, particularly those involving search. However, interpretability challenges persist, especially in explaining obtaine...
arxiv.org