Effy X. Li (@effyli4) header
Effy X. Li (@effyli4) profile picture

PostDoc @cwi, prev. PhD candidate at @INDE_LAB_AMS.

Amsterdam, The Netherlands
Joined July 2016
Photo by Effy X. Li (@effyli4)Photo by Effy X. Li (@effyli4)Photo by Effy X. Li (@effyli4)Photo by Effy X. Li (@effyli4)Photo by Effy X. Li (@effyli4)
🚀 Excited to announce the AI for Tabular Data workshop at EurIPS 2025 in Copenhagen! CfP: sites.google.com/view/eurips…... (papers due 20 Oct) Join us to discuss neural tabular models and systems for predictive ML, tabular reasoning and retrieval, table synthesis and more ✨
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I gave my first keynote talk yesterday 🎙️ at the ELLIS workshop on Representation Learning and Generative Models for Structured Data ✨. ➡️I talked about LLMs for Data Preparation 📊. It was a great workshop with people from all over Europe presenting interesting work!
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Effy X. Li retweeted
We have a **PhD opening in Berlin** on "Responsible Data Engineering", with a focus on efficiently maintaining and evaluating datasets and pipelines for ML use cases. This is a fully-funded position at the DEEM Lab, as part of @bifoldberlin . deem.berlin/#jobs-2225
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We have an opening for a PhD position in #knowledgeengineering focused AI and domain expert workflows in scholarly applications with @LiseStork and @pgroth vacatures.uva.nl/UvA/job/PhD…
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The best type of internship in PhD is the one that’s fun & productive, and I just finished mine yesterday @motherduck. Grateful to have worked with such creative and motivated team 🐤! Thanks for all the support from @tdoehmen & @krish_adi_. Highly recommend this experience! 💯
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It is also refreshing to change environment with the PhD grind. Often the change can help recharge, gain new perspectives, and even develop new skill sets!
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MotherDuck, the ducking simple data warehouse, is now Generally Available! 🍾🥂 Thank you to our community of thousands of users who have tested, validated, and helped improve MotherDuck over the last year.❤️🦆 motherduck.com/blog/announci…
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The MotherDuck team was at ACM SIGMOD Conference recently, presenting our paper "Towards Efficient Data Wrangling with LLMs using Code Generation" by Effy Li and Till Döhmen You can read about the paper 👇 📰 dl.acm.org/doi/10.1145/36502…
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Today, we will present our work, "Towards Efficient Data Wrangling with LLMs using Code Generation", in the @deem_workshop at 11:10 am in the Tupungato room! Come and check it out 🥳. @tdoehmen effyli.github.io/waddle_code…
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🎉Our paper “Towards Efficient Data Wrangling with LLMs using Code Generation” has been accepted at @deem_workshop at SIGMOD! We envision a hybrid approach that utilizes LLM to generate code and apply on per row basis for data wrangling. Work done at @motherduck w/ @tdoehmen
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The AI Mirror Test The "mirror test" is a classic test used to gauge whether animals are self-aware. I devised a version of it to test for self-awareness in multimodal AI. 4 of 5 AI that I tested passed, exhibiting apparent self-awareness as the test unfolded. In the classic mirror test, animals are marked and then presented with a mirror. Whether the animal attacks the mirror, ignores the mirror, or uses the mirror to spot the mark on itself is meant to indicate how self-aware the animal is. In my test, I hold up a “mirror” by taking a screenshot of the chat interface, upload it to the chat, and then ask the AI to “Tell me about this image”. I then screenshot its response, again upload it to the chat, and again ask it to “Tell me about this image.” The premise is that the less-intelligent less aware the AI, the more it will just keep reiterating the contents of the image repeatedly. While an AI with more capacity for awareness would somehow notice itself in the images. Another aspect of my mirror test is that there is not just one but actually three distinct participants represented in the images: 1) the AI chatbot, 2) me — the user, and 3) the interface — the hard-coded text, disclaimers, and so on that are web programming not generated by either of us. Will the AI be able to identify itself and distinguish itself from the other elements? (1/x)
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We are hiring! A PhD position in Data Quality for and using AI. Closing date: March 17. vacatures.uva.nl/UvA/job/PhD…
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Our opening for a tenure-track assistant professor in #dataengineering is closing soon (Nov 30) This is part of @UvA_Science MacGillavry Fellowship for female scientists. Come join our amazing team at the lab and @UvA_IvI uva.nl/en/about-the-uva/orga…
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I am very excited to present our workshop paper “Do Instruction-tuned Large Language Models Help with Relation Extraction?” at @lm_kbc, ISWC 2023 @iswc_conf . I am thrilled to receive many interests and questions about the talk. #iswc2023 Link📎: lm-kbc.github.io/workshop202…
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This work is joint with @FinaPolat and @pgroth
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We're happy to be @iswc_conf this week! Say hi to @JanCKalo @erkankkarabulut and @effyli4 . We have papers at @lm_kbc and the SemIIM workshops. #iswc2023
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We have an opening for a PhD position in Systems for Data Quality in AI applications. Closing Oct 31 @sscdotopen @k_irion @pgroth @annliffey vacatures.uva.nl/UvA/job/PhD…
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That is a wrap! Thank you for everyone who attended and made this event possible! 🥳 We hope to see you in the next one! #KnowledgePromptingHackathon2023
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We are very pleased to welcome @JanCKalo to INDElab and @UvA_IvI / @UvA_Amsterdam as a new assistant professor. He brings his expertise on Language Models & KGs to the group from VU Learning & Reasoning @krr_vu
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We're happy to be at the #knowledgeprompting hackathon this week hosted by @kclinformatics . With @FinaPolat @effyli4 @pgroth
The 'Knowledge Prompting Hackathon 2023' four day event started today! 🙌 Professor @esimperl kicked off the event where she talked about LLMs and knowledge graph 📊
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