
Rob van der Goot
@robvanderg
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RT @NoSyu: Have a Findings paper accepted at #NAACL2025? 🎉 .Share your work at the W-NUT Workshop! .You can submit your info via the form b….
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RT @NoSyu: CfP: W-NUT 2025 @naaclmeeting.Topics: NLP tasks over user-generated text, such as that found on social media, online reviews, or….
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RT @NoSyu: We also host MultiLexNorm 2: a shared task on multi-lingual lexical normalization focusing on non-Indo-european languages. https….
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RT @NoSyu: Call for Papers: The 10th Workshop on Noisy and User-generated Text (W-NUT) @ #NAACL2025.The WNUT workshop focuses on NLP tasks….
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RT @annargrs: 📢 Looking for a PhD student to start in Sep 2024! Applications due April 15. This project is about LLM competence in interpre….
candidate.hr-manager.net
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Workshop on Noisy and User-Generated Text (WNUT) is collocated with EACL (@eacmeeting) this year, Looking forward to your submissions!, .submission deadline: 18th of December.
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RT @mxmeij: Introducing. the Subspace Chronicles (ft. @robvanderg, @barbara_plank, @iatitov)—a riveting tale of linguistic information em….
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Updated my website, and now finally you can reply to my "blogs" (! Looking forward to see if anyone cares enough to start a discussion there!.
robvanderg.github.io
The homepage of Rob van der Goot, containing all his interesting and his less interesting work.
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RT @pinartozun: More info on RAD-day (Feb 13, 11am-3pm CET) talks is now available at Thanks Rob van der Goot @rob….
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RT @barbara_plank: On-going now: VarDial@EACL 2023 shared tasks, incl. slot & intent detection for low-res lang varieties (SID4LR) .@noemin….
sites.google.com
The VarDial workshop has a history of hosting well-attended shared tasks on various dialects and languages - see the recent campaign reports from 2022 and 2021. In VarDial 2023 we are organizing the...
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RT @GroNlp: Full room for @robvanderg's talk in our research seminar today! It's been great to have him back with us for a week, and to hea….
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RT @Sajawel_A: I’m happy to share that our paper “Tafsir Dataset: A Novel Multi-Task Benchmark for Named Entity Recognition and Topic Model….
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Ok, fair enough, a large transformer model still ranked highest. But they had to do some interesting things to get there! Congrats to David Samuel and @straka_milan ( as well as all other participants!, many interesting approaches were used.
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