Yannis Konstas

111 posts

Yannis Konstas

Yannis Konstas

@sinantie

Associate Professor of Computer Science at Heriot-Watt University & Head of ML and Co-founder at Alana @HeriotWattUni. Researching #NLG #NLProc #NLP

Edinburgh, Scotland Katılım Şubat 2009
397 Takip Edilen366 Takipçiler
Yannis Konstas
Yannis Konstas@sinantie·
Looking for a cool place to work on NLP, Generative AI, Robotics, ML (among other things)? Join us as an Assistant Professor at HWU; there is still time to apply! Deadline extended to 11/5/2025. linkedin.com/jobs/view/4205…
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Nikolas V. 🦋
Nikolas V. 🦋@NikVits·
So very, very proud to share our new paper “Voices in a Crowd: Searching for Clusters of Unique Perspectives” (arXiv:2407.14259), a novel framework on how to organically find clusters of unique voices (perspectives) in datasets. 🧵 for summary, co-authors @amitkparekh_ @sinantie
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Alana
Alana@helloalana·
Exciting news! We are now working with University Hospitals of Derby and Burton NHS Foundation Trust to help clinicians quickly access and search the latest medical guidelines. Faster, smarter medical support is coming! @NHS
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Athens NLP Summer School
Athens NLP Summer School@AthensNLP·
📢WE ARE BACK!💥 It's official! The Athens Natural Language Processing Summer School @AthensNlp is taking place in 2024 in Athens Greece 🇬🇷! 📅Save the dates 19 - 25 September 2024. Use #AthNLP2024 for updates!
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Yannis Konstas
Yannis Konstas@sinantie·
I am really excited to be giving a TEDx Youth talk on online Gender-Based Violence and AI/NLP. Thanks a lot, #TEDxYouthStGeorgesEdinburgh for hosting. Special thanks to @GerrardPoppy and @NikVits for the discussions to prepare the talk! #VoicesOfTheFuture #tedxstge.
St George's School, Edinburgh@stgeorgesedin

🌟📣 Announcing our #TEDxYouthStGeorgesEdinburgh #VoicesOfTheFuture 2024 speaker lineup! We're excited to welcome Yannis Konstas to the #TEDxYouth stage.💻Follow TEDx Youth St Georges Edinburgh on Facebook for more updates 👉👉 ow.ly/xRqC50QOrfI #IdeasWorthSpreading #TEDx

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Alessandro Suglia
Alessandro Suglia@ale_suglia·
Our survey paper is now available on @JAIR_Editor: jair.org/index.php/jair… Many thanks to my co-authors @oliverlemon and @sinantie for supporting me in this great effort! Looking forward to hearing your feedback, especially on the future research directions section!
Alessandro Suglia@ale_suglia

Another great news today: our survey paper "Visually Grounded Language Learning: a review of language games, datasets, tasks and models" was accepted by JAIR. This was part of my PhD thesis completed under the supervision of @oliverlemon and @sinantie!

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Fazl Barez
Fazl Barez@FazlBarez·
New Paper 🎉: arxiv.org/pdf/2401.01814… Can language models relearn removed concepts? Model editing aims to eliminate unwanted concepts through neuron pruning. LLMs demonstrate a remarkable capacity to adapt and regain conceptual representations which have been removed 🧵1/8
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Interaction Lab
Interaction Lab@iLab_hwu·
Welcome to iLab Wrapped!!🎉🎉 It's the end of 2023, so let's take a dive into some of the Interaction Lab's papers. Please follow your favourite authors so you can keep up with their work beyond their time at @iLab_hwu (apologies if the thread updates slowly - @Addlesee_AI)
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Fazl Barez
Fazl Barez@FazlBarez·
🎉 New paper to appear at ACL 2023 : arxiv.org/abs/2305.17553 Large Language Models (LLMs) are powerful tools, but they can memorize false or outdated associations. Model editing techniques promise to solve this, but do they really work? 1/
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Antonio Valerio Miceli Barone
Antonio Valerio Miceli Barone@AVMiceliBarone·
New paper: arxiv.org/abs/2305.15507 LLMs are good at programing tasks, and they are now being widely used to assist code generation. But do they actually understand the semantics of programming languages, or do they rely on superficial, "shortcut" correlations? Let's find out! 1/
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Yannis Konstas
Yannis Konstas@sinantie·
The full paper will be available to the community very soon, so stay tuned! 3/3
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Yannis Konstas@sinantie·
We use open-domain question answering systems as our test-bed for task based dialog generation and compare several models, with a focus on highlighting the danger of systems that appear to be trustworthy by "parroting" user input while providing an unfaithful response. 2/3
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