Ivan Titov @iatitov
Professor of Natural Language Processing at Uni Edinburgh / Uni Amsterdam ivan-titov.org Edinburgh, Scotland Joined September 2016-
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PhD opening at the University of Amsterdam to work on AI/NLP/IR technology for information access. We work on LLMs for scholarly research and investigative journalism. Interested? See project 1 in: vacatures.uva.nl/UvA/job/4PhDs/… @AmsterdamNLP #phd #ir #nlp #ai #amsterdamjobs
Classical mixture models are limited to positive weights and this requires learning very large mixtures! Can we learn (deep) mixtures with negative weights? Answer in our #ICLR2024 spotlight by @loreloc_ Aleks, Martin, Stefan, Nicolas @arnosolin 📜openreview.net/forum?id=xIHi5…
Classical mixture models are limited to positive weights and this requires learning very large mixtures! Can we learn (deep) mixtures with negative weights? Answer in our #ICLR2024 spotlight by @loreloc_ Aleks, Martin, Stefan, Nicolas @arnosolin 📜openreview.net/forum?id=xIHi5… https://t.co/qDglZQitpU
📽️: tinyurl.com/2f2u8bcd Poster: tinyurl.com/vm5n9mf5 Code: tinyurl.com/357atb6v Visualisation: tinyurl.com/3e6kbz6m Work with @tetraduzione and Adam Lopez, accepted at #AAAI2024. (+/7)
I am still looking for PhD students starting in September 2024! The deadline to apply for the CDT in NLP is the 11th of March. If you wish to do research in modular and efficient LLMs, here are some highlights of my lab's research from the past year ⬇️🧵
I am still looking for PhD students starting in September 2024! The deadline to apply for the CDT in NLP is the 11th of March. If you wish to do research in modular and efficient LLMs, here are some highlights of my lab's research from the past year ⬇️🧵
Interested in training with future leaders in NLP to engage with the cutting edge of the technical, social, design, and legal aspects of these systems? Then apply for our new Centre for Doctoral Training in Designing Responsible NLP! Deadline 11 March 2024 responsiblenlp.org/2024-studentsh…
Looking for an intern to work on LLM interpretability; FAIR at Meta, London metacareers.com/jobs/346318094…
Interested in multimodal fact-checking? Apply for a postdoc position with @MichaelSejr @ZhijiangG and me: jobs.cam.ac.uk/job/44672/ Deadline for applications is 25/1!
Last week, I presented my thesis at @GenBench #EMNLP2023 - the last step of my Masters journey at @EdinburghUni. I feel honoured to have worked with @vernadankers and @iatitov! And I am proud to have received the Howe Prize for the best student in the AI Masters. Miss u Edinburgh
We often talk about compositional generalization but can we get human ratings of (non-)compositionality for NL sentences? Check @vernadankers and Chris Lucas' paper on non-compositionality in sentiment just presented at #EMNLP2023 arxiv.org/abs/2310.20656
We often talk about compositional generalization but can we get human ratings of (non-)compositionality for NL sentences? Check @vernadankers and Chris Lucas' paper on non-compositionality in sentiment just presented at #EMNLP2023 arxiv.org/abs/2310.20656 https://t.co/EBFxfeN8Qn
Verna presenting Memorisation Cartography paper at #EMNLP2023 Check arxiv.org/pdf/2311.05379 if you'd like to learn about memorization in machine translation
Verna presenting Memorisation Cartography paper at #EMNLP2023 Check arxiv.org/pdf/2311.05379 if you'd like to learn about memorization in machine translation https://t.co/gP1QsKMc9W
At 11AM in PS5, I'll be presenting "Memorisation cartography: Mapping out the memorisation-generalisation continuum in neural machine translation" arxiv.org/pdf/2311.05379 with dream team @iatitov & @_dieuwke_. Memorisation in neural networks is concerning but also needed... (1/5)
we show how many of the popular losses used to train #knowlege #graph #embeddings can be understood as special cases of a weighted composite #likelihood. This helps understand #why they work (and why they are better than negative sampling) and design new principled variants!
we show how many of the popular losses used to train #knowlege #graph #embeddings can be understood as special cases of a weighted composite #likelihood. This helps understand #why they work (and why they are better than negative sampling) and design new principled variants!
I’m hiring a postdoc for my VIDI project on improving modeling of low-res morphologically rich languages taking inspiration from child language acquisition insights. Are you the one? Come talk to me at #EMNLP2023! (more details here: cs.rug.nl/~bisazza/)
I’m hiring a postdoc for my VIDI project on improving modeling of low-res morphologically rich languages taking inspiration from child language acquisition insights. Are you the one? Come talk to me at #EMNLP2023! (more details here: cs.rug.nl/~bisazza/)
Today at BlackboxNLP (11AM, east foyer), and Saturday at 9AM in PS4: "Non-Compositionality in Sentiment: New Data and Analyses" by Chris Lucas & I!🙋♀️
Today at BlackboxNLP (11AM, east foyer), and Saturday at 9AM in PS4: "Non-Compositionality in Sentiment: New Data and Analyses" by Chris Lucas & I!🙋♀️
Today at 4PM @MaikeZufle will present "Latent Feature-based Data Splits to Improve Generalisation Evaluation: A Hate Speech Detection Case Study" at the GenBench poster session in the east foyer! In this work (arxiv.org/pdf/2311.10236…) Maike, @iatitov and I present... (1/5)
I and @iatitov are organising an @ELLISforEurope #NeurIPS2023 fest in #Edinburgh where people can show & discuss the latest #ML and #AI research done at @InfAtEd This Friday from 11am 👉web.inf.ed.ac.uk/ellis-edinburg…
SCALE-LLM - a new workshop! Join us at EACL 2024 :) scale-llm-24.pages.dev #NLProc #EACL2024 @eaclmeeting
SCALE-LLM - a new workshop! Join us at EACL 2024 :) scale-llm-24.pages.dev #NLProc #EACL2024 @eaclmeeting https://t.co/qEQyuXw4Az
Reposting here: Open position for Lecturer/Reader in Machine Learning (~Asst/Assoc Prof). The position is full-time and open-ended (equivalent to a US tenured position). Where: School of Informatics at the University of Edinburgh, UK. How: Apply here - elxw.fa.em3.oraclecloud.com/hcmUI/Candidat…
Introducing... the Subspace Chronicles (ft. @robvanderg, @barbara_plank, @iatitov)—a riveting tale of linguistic information emerging, shifting and disentangling across LM training! Coming to an #EMNLP2023 near you! 📜⏳ 📑personads.me/x/emnlp-2023-p… 📽personads.me/x/emnlp-2023-v…
Happy to announce that @InfAtEd are recruiting a professor in NLP, computer vision, or ML to lead our brand-new Laboratory for Generative AI. Deadline 16 Feb 2024. aspenpeople.co.uk/microsite/uoe-…
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1K Followers 221 Following The #SapienzaNLP group led by @RNavigli at the #Sapienza University of #Rome conducting #research in multilingual #NLProc. Strong connection to @Babelscape!
Last week we had a very inspiring @ELLISforEurope Natural Language Processing workshop at the Mathematisches Forschungsinstitut Overwolfach (MFO). Thanks @raquel_dmg and @sandropezzelle for organizing it!
Thanks Andre @iatitov @IGurevych and @ELLISforEurope for proposing and supporting the organization of this workshop! It was a pleasure to make it happen together with @raquel_dmg and all participants 🔥 #NLProc #AI #MFO #ELLIS
Last week we had a very inspiring @ELLISforEurope Natural Language Processing workshop at the Mathematisches Forschungsinstitut Overwolfach (MFO). Thanks @raquel_dmg and @sandropezzelle for organizing it!
Amazing work, @soheeyang_ et al.!! Thank you, @KassnerNora, for talking about this work last week at @InfAtEd 🙂 Paper: Do Large Language Models Latently Perform Multi-Hop Reasoning? arxiv.org/abs/2402.16837
Google announces Do Large Language Models Latently Perform Multi-Hop Reasoning? study whether Large Language Models (LLMs) latently perform multi-hop reasoning with complex prompts such as "The mother of the singer of 'Superstition' is". We look for evidence of a latent…
📽️: tinyurl.com/2f2u8bcd Poster: tinyurl.com/vm5n9mf5 Code: tinyurl.com/357atb6v Visualisation: tinyurl.com/3e6kbz6m Work with @tetraduzione and Adam Lopez, accepted at #AAAI2024. (+/7)
It is funded by Arianna's VIDI project, and located at @GroNlp, which is a great place - In fact I look forward to visiting my alma mater next week :) - back then, there was no cow logo yet ;-)
Arthur’s Seat view from Informatics’ terrace serves as a refresh button during my break times! Very enjoying my visit w/ @iatitov and his team at @EdinburghNLP!
congrats to Dr. @EmilevanKrieken who successfully defended his #PhD thesis "#Optimization in #Neurosymbolic #Learning Systems" (research.vu.nl/en/publication…) obtaining a cum laude from @VUamsterdam! #ML #AI #NeSy
Looking for an intern to work on LLM interpretability; FAIR at Meta, London metacareers.com/jobs/346318094…
I'm excited to announce that I've joined @cohere to help make LLMs more multilingual! It’s crazy how the capabilities of NLP models have evolved over the last years. I’m thrilled to work with a team full of smart, dedicated and kind individuals to push the boundaries of LLMs.
🌟Exciting news alert! 🌟 I am beyond thrilled to share that in January I am joining @HelmholtzMunich as a director & @TU_Muenchen as a Liesel Beckman distinguished professor! This opportunity marks an incredible leap in my career journey, one I'm deeply grateful for.
I still remember when exposure bias meant that the model was never trained on its own rollouts and was something that imitation learning was supposed to fix.
Large Language Models have Exposure Bias. Exposure Bias happens when one LLM gets more exposure to users (regardless of the intrinsic model quality) via social media. This results in more users exploring its API, building illustrative examples for each other, and increasing…
Yay, I got my first grant! 🙏@DFF_raad I'll be looking for a postdoc to work on an ambitious generalization benchmark, in collaboration with @tallinzen. If you'd like to spend a year in beautiful Copenhagen - please reach out! (email preferred) Could start as early as February.
Last week, I presented my thesis at @GenBench #EMNLP2023 - the last step of my Masters journey at @EdinburghUni. I feel honoured to have worked with @vernadankers and @iatitov! And I am proud to have received the Howe Prize for the best student in the AI Masters. Miss u Edinburgh
The #Edinburgh @InfAtEd crew at @NeurIPSConf decompressing! including @henrygouk @loreloc_ @EmilevanKrieken @LaurenNDeLong @bryanlimy @vsimkus and with bonus photo bombing by @jmtomczak!
I am truly delighted and humbled to be elected as a Fellow of ACL - the premier scientific society in NLP. ACL is an amazing community, and I am particularly honoured to be selected alongside the incredible @MonaDiab77, @RNavigli, Barbara Di Eugenieo and Ming Zhou!
Association for Computational Linguistics is delighted to announce that the ACL Nominating Committee has selected five ACL fellows for 2023: #NLProc
Even more grateful to also receive an Outstanding Paper Award at #EMNLP2023 for our paper on cross-lingual consistency of factual knowledge in LMs! with @Jirui_Qi and @raquel_dmg. @GroNlp @AmsterdamNLP arxiv.org/abs/2310.10378
Very grateful for this @GenBench award given to our work on measuring cross-lingual consistency of factual knowledge in LMs w/ @Jirui_Qi and @raquel_dmg!
Best short paper is about minimum Bayes risk decoding. #EMNLP2023
Julius did amazing work! Very happy about this award, thank you!
EMNLP 2023 Best Short Paper Faster Minimum Bayes Risk Decoding with Confidence-based Pruning (Julius Cheng, Andreas Vlachos) aclanthology.org/2023.emnlp-mai… #EMNLP2023 #NLProc
We convert popular knowledge graph embedding (KGE) models such as ComplEx into generative models of triples that 1️⃣ better scale training to very large knowledge graphs 2️⃣ make reliable predictions with logical constraints 3️⃣ support sampling in our #NeurIPS2023 oral!
we show how many of the popular losses used to train #knowlege #graph #embeddings can be understood as special cases of a weighted composite #likelihood. This helps understand #why they work (and why they are better than negative sampling) and design new principled variants!
GeKCs can be learned via the same discriminative objectives used with KGE models. In our work we generalize them as pseudo-log-likelihoods, which is an efficient alternative to the maximum-likelihood estimation (MLE) objective. We show learning by MLE is efficient only for GeKCs!
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