- Agentic Data Science
- LLMs for Data Management
- LLMs for Information Extraction
~/about
Effy Xue Li.
Postdoctoral Researcher at CWI Amsterdam.
Working on Agentic Data Science, LLMs for Data Management and LLMs for Information Extraction.

Latest news
updated Oct 2026- Oct 2026 new I gave a talk on The Silent Failures in Agentic Data Science at the SODA team, Inria Saclay.
- Oct 2026 New preprint: The Silent Failures in Agentic Data Science. Data science agents often look good on accuracy while hiding failures such as data leakage.
- Jul 2026 New preprint: Beyond Scale and Generation: Understanding Language Model-based Entity Matching.
show older news (12)
- Dec 2025 I co-organized the AI for Tabular Data workshop at EurIPS 2025 in Copenhagen.
- Apr 2025 I was at Dagstuhl seminar on Challenges and Opportunities of Table Representation Learning, and I gave a talk on Context Matters in TRL (pdf).
- Feb 2025 I gave my first keynote talk on Efficient Use of LLMs for Data Preparation, at ELLIS workshop on Representation Learning and Generative Models for Structured Data
- Jan 2025 I was at CIDR'25, Amsterdam as a volunteer
- Aug 2024 I was at VLDB'24, Guangzhou China. Here is my trip report
- Jul 2024 Our paper titled ‘How different is different? Systematically identifying distribution shifts and their impacts in NER datasets’ got accepted to Language Resources and Evaluation (LREC)!
- May 2024 Our paper titled ‘Towards Efficient Data Wrangling with LLMs using Code Generation’ got accepted to DEEM@SIGMOD'24! I will be in Chile to present our work.
- Aug 2023 Our paper titled ‘Do Instruction-tuned Large Language Models Help with Relation Extraction?’ got accepted to ISWC LM-KBC workshop!
- Aug 2023 Our team scored 2nd on the LM-KBC challenge on Track 2!
- Aug 2023 I joined the Knowledge Prompting Hackathon at KCL, London.
- Mar 2023 I gave a talk named ‘Large Language Models in Standards Discourse Analysis’ at IETF116-RASPRG, remotely. Recording on Youtube is here, from 1:18:50
- Mar 2023 A preprint titled ‘How different is different? Systematically identifying distribution shifts and their impacts in NER datasets’ now is out here
Hi! I’m Effy, you can also call me 李雪 [lǐ xuě]. I am a Postdoctoral Researcher at CWI Amsterdam, in the TRL lab, led by dr. ir. Madelon Hulsebos. I am interested in the topic of evaluating and building Agentic Data Science.
I did my PhD at University of Amsterdam in INDE lab, supervised by Prof. Paul Groth and Dr. Jan-Christoph Kalo. During my PhD, I did an internship at MotherDuck on data wrangling with LLMs. Previously I was an AI resident at Microsoft Research Cambridge, UK. Before that I did my Master’s at University of Edinburgh.
My PhD topic was on Knowledge Graph Construction from Conversational Data. Specifically, I look into how we can better utilize (large) language models to extract information such as entities and relations, and furthermore, make (large) language models more data-efficient, robust and adaptable. My PhD research was funded and situated in an NWO project IN-SIGHT.it.
I am originally from China and have lived in the UK and the Netherlands. When I am not in front of my laptop, you can often find me bouldering (at a complete beginner level), cycling or drinking coffee (like everyone else :D). If you are keen to collaborate or exchange ideas over a coffee, you can reach out to me at effy DOT li AT cwi DOT nl.
- 2025–now
Postdoctoral Researcher
CWI Amsterdam
Agentic Data Science. - 2020–2025
Ph.D., Knowledge Graph Construction
University of Amsterdam
Supervised by Prof.Paul Groth and Dr.Jan-Christoph Kalo. - 2017–2018
M.Sc., Artificial Intelligence
University of Edinburgh
Supervised by Prof. Shay Cohen. - 2012–2016
B.Eng., Electronic Information Engineering
Guangzhou University
Graduated with top 1% GPA with National Scholarship.
- 2024
Intern
MotherDuck
Data wrangling with LLMs. - 2018–2019
AI Resident
Microsoft Research Cambridge, UK
API misuse detection with graph neural networks on source code; neural ranking for enterprise search. - 2016–2017
Front-end Engineer
Guangzhou Wuliudian Education Consulting
WeChat mini program, company homepage, UI and visual design.
- 2026
The Silent Failures in Agentic Data Science
arXiv preprint [paper] [pdf] [project] - 2026
Beyond Scale and Generation: Understanding Language Model-based Entity Matching
arXiv preprint, under review [code] [paper] [pdf] - 2025
Towards a Controllable and Realistic Entity Matching Benchmark
DBDBD'25 - 2025
Evaluation of Unsupervised Static Topic Models' Emergence Detection Ability
PeerJ Computer Science [paper] [pdf] - 2025
Position: Unlocking the Full Potential of Data Science Requires Tabular Foundation Models, Agents, and Humans
Position paper, preprint [paper] [pdf] - 2024
How different is different? Systematically identifying distribution shifts and their impacts in NER datasets
Language Resources and Evaluation (LREC) [paper] - 2024
Towards Efficient Data Wrangling with LLMs using Code Generation
DEEM@SIGMOD'24 [code] [pdf] [poster] - 2023
Knowledge-centric Prompt Composition for Knowledge Base Construction from Pre-trained Language Models
ISWC 2023 LM-KBC workshop [code] [pdf] [poster] - 2023
Do Instruction-tuned Large Language Models Help with Relation Extraction?
ISWC 2023 LM-KBC workshop [pdf] - 2021
The Challenges of Cross-Document Coreference Resolution for Email
Proceedings of the 11th Knowledge Capture Conference [pdf]
- 2026–27 PC Member, ICDE 2026, ICDE 2027
- 2026 Proceedings Co-chair, SIGMOD 2026
- 2025 Co-organizer, AI for Tabular Data workshop @ EurIPS 2025
- Jan – Jul 2026
Student supervision
Student: Hongqian Xia
Why do Data Science Agents fail? - Oct – Dec 2023 Teaching Assistant, NLP1, UvA
- Jan – Jul 2023
Master thesis supervision
Student: Casper Smit
Graphical information for cross-document coreference resolution in emails [student] - Apr – May 2023 Teaching Assistant, Data and Knowledge, UvA
- Jan – Jun 2022
Master thesis supervision
Student: Timothy Dorr
Not All Names Are WEIRD: Identifying Name Origin Bias in Named Entity Recognition Tasks on Email Data [student] [thesis] - Feb – Apr 2022 Teaching Assistant, Causal Data Science, UvA