Madelon Hulsebos 🦋 madelonhulsebos.bsky.social
@MadelonHulsebosResearching neural models for structured data; table representation learning💫; faculty @cwinl member @ellisforeurope, prev @berkeley_eecs @uva_amsterdam
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Tables are a goldmine for accurate, fresh, domain data that LLMs should be grounded in for RAG, factver/QA, text2sql: retrieval is key! We introduce 🎯TARGET, a benchmark for evaluating table retrieval! Code,data,paper: target-benchmark.github.io Thinking bm25 ftw? Think twice..🧵
I'm now also on bluesky 🦋 bsky.app/profile/madelo…. Will just duplicate for now, but feels pretty promising!
- Read more in the paper: arxiv.org/abs/2406.19380… - Use TabReD in your new method evals: github.com/yandex-researc… - Follow other people who are doing great work in this direction: @__smarton @__mfeurer__ @jpgard @MadelonHulsebos @TrlWorkshop <|eos|>
Tabular DL success on benchmarks ≠ success in production. We know this first hand, trying to ship models. This motivated us to create TabReD - a new suite of 8 tabular datasets that capture real-world data characteristics overlooked by existing benchmarks. (1/N)
As @wenhuchen once put it: “...if your retrieval is mediocre, your LLM can easily backfire”. We should not overlook the value of structured data! Let's work on better retrieval for structured data; contrib and eval new table retrievers w 🎯TARGET target-benchmark.github.io. 6/6
Tables are a goldmine for accurate, fresh, domain data that LLMs should be grounded in for RAG, factver/QA, text2sql: retrieval is key! We introduce 🎯TARGET, a benchmark for evaluating table retrieval! Code,data,paper: target-benchmark.github.io Thinking bm25 ftw? Think twice..🧵
Check out our newest workshop paper: TARGET: Benchmarking Table Retrieval for Generative Tasks This marks my first academic publication, and I'm super grateful for the guidance from @MadelonHulsebos and @adityagp Thank you for making this such a rewarding and fun experience!
Tables are a goldmine for accurate, fresh, domain data that LLMs should be grounded in for RAG, factver/QA, text2sql: retrieval is key! We introduce 🎯TARGET, a benchmark for evaluating table retrieval! Code,data,paper: target-benchmark.github.io Thinking bm25 ftw? Think twice..🧵
🎦 Watch the recording of Madelon Hulsebos's seminar at BIDS! "There is actually a lot of structured data available on the web.... But really, the task here is that we should be able to retrieve that easily." #datascience #structureddata #dataretrieval bids.berkeley.edu/news/madelon-h…
Open-rank search (unusual for EECS) - please RT and apply!
EECS is hiring! Open faculty positions are now available. We welcome applicants from all areas focusing on originality and research promise. Join us in shaping the future of EECS! #UCBerkeley #EECS 🔗 More info: bit.ly/3AaLZdY 🔗 bit.ly/3YgWDb6
Our paper, "Data Void Exploits: Tracking & Mitigation Strategies," has just received the Best Paper Award at @cikm2024 ! 🏆 Data voids are gaps in online information, which are often exploit to spread disinformation. More details 👇 #CIKM2024 #DataVoids #Disinformation #KGs
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Who to follow
-
Dutch Seminar on Data Systems Design
@dsdsdnl -
Stefan Grafberger
@SGrafberger -
Andreas Kipf
@andreaskipf -
Anna Fariha
@FarihaAnna -
Peter Boncz
@peterabcz -
SIGMOD/PODS 2025
@SIGMODConf -
Table Representation Learning @NeurIPS
@TrlWorkshop -
Sebastian
@sscdotopen -
Calc Consulting
@CalcCon -
Immanuel Trummer
@ImmanuelTrummer -
Carsten Binnig
@cbinnig -
CIDR 2025
@cidrdb -
Matthias Boehm
@matthiasboehm7 -
Intelligent Data Engineering Lab
@INDE_LAB_AMS -
Pınar Tözün (@[email protected])
@pinartozun
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