David Vos

Information retrieval and generative modelling. PhD candidate @irlab_amsterdam with @mdr and @HarrieOos. Prev. @INDE_LAB_AMS and @DPGMediaAI.

[David Vos @dja_vos]

Had an extremely inspiring day presenting my work yesterday at #NeurIPS2022 @TrlWorkshop. Big thanks to the organisers and attendees.

We also won the best paper runner-up award with our work on prefix-tuning for data wrangling tasks 🥳

[Sumit @_reachsumit]

Efficient Optimization of Hierarchical Identifiers for Generative Recommendation

Proposes greedy & hybrid tree construction methods that reduce identifier building time to 2-8% while maintaining or improving retrieval quality.

📝https://t.co/qxJ3xpXCsp
👨🏽‍💻https://t.co/gchrBGoFU9

[David Vos @dja_vos]

Proud supervisor moment :)

Do you need hierarchical identifiers for generative recommendations? You can actually be very efficient in your tree building 🧐

Work we did with excellent students from the RecSys course at @irlab_amsterdam. We’ll be presenting at ECIR 2026!

[Sumit @_reachsumit]

Efficient Optimization of Hierarchical Identifiers for Generative Recommendation

Proposes greedy & hybrid tree construction methods that reduce identifier building time to 2-8% while maintaining or improving retrieval quality.

📝https://t.co/qxJ3xpXCsp
👨🏽‍💻https://t.co/gchrBGoFU9

[David Vos @dja_vos]

We shed some light on what language model you should use for your next news recommender system!

[Sumit @_reachsumit]

Revisiting Language Models in Neural News Recommender Systems

Studies the impact of language model sizes in news recommendation, finding that larger models don't always improve performance but help more with cold-start users.

📝https://t.co/fNHUbu70KB

[David W. Romero @davidwromero]

Very happy to share my first project at NVIDIA! 🚀

We present Meshtron, a pure Transformer model that consistently reasons over 500k+ tokens to generate 3D meshes of outstanding quality.

Webpage: https://t.co/yiRoZpPn6j

w/ @zekunhao19951 @TsungYiLinCV & @liu_mingyu

🧵

[David Vos @dja_vos]

Honored to be Zihan’s paranymph!

[Zhaochun Ren @zhaochun_ren]

Congratulations to Zihan @ZihanWa54274484 on successfully passing his PhD defense today!

[David Vos @dja_vos]

I moved to https://t.co/gPgLSMEtDp. It's really nice over there, I think you should try it!

[Verna Dankers @vernadankers]

My "looking for a postdoc" stickers and I are in Miami for #EMNLP2024! 🤩 Do you have/know of a postdoc for summer/autumn '25 related to interpretability, figlang and/or memorisation (vs generalisation)? Reach out! Looking forward to #GenBench2024 on Saturday and the many many...

[David Vos @dja_vos]

Want to work on search for (news) media at one of the biggest publishers in the Netherlands? @DPGMediaIT is looking for an addition to their team. Great opportunity in my opinion: https://t.co/jRnKJnH3Fc

[David M. Knigge @davidmknigge]

🇨🇦 Deeeelighted to share that this work got into #neurips2024. Many thanks to my dear friend and co-author @Dafidofff, as well as the rest of the team.

Solving PDEs in continuous space-time with Neural Fields on cool geometries while respecting their inherent symmetries! 💫💫

[ELLIS Amsterdam @Ellis_Amsterdam]

15th @ELLISforEurope @essir_eu Summer School on #informationretrieval was held from 1-5 July 2024 @irlab_amsterdam of the @UvA_Amsterdam 🚀

The ELLIS flagship school is the largest ESSIR organized so far and the first ESSIR to include a hackathon✨

🔗https://t.co/B4pulNNjUI

[ELLIS Amsterdam @Ellis_Amsterdam]

The Search Engines Amsterdam Meetup @irlab_amsterdam is back ✨ followed by drinks🍻

📆 Fri, Oct 4th
📍Lab42, room L3.33
⏰16.00
🚀James Allan (UMass) will talk about Probing Ranking LLMs: Mechanistic Interpretability in Information Retrieval

🔗https://t.co/aTgWT3Tpo1

[David Vos @dja_vos]

Here’s a picture to prove I was actually on stage! And special thanks to @rmpetcu for so eloquently introducing the Attention Mechanism :)

[David Vos @dja_vos]

Got to give a lecture on Transformers in the amazing Amsterdam Tuschinski theatre. Also gave @3blue1brown the screen real estate he really deserves 😊

[Mohammad Aliannejadi @maliannejadi]

Listening to @IR_oldie talking about challenges and opportunities in evaluating generative IR.

[David Vos @dja_vos]

@christine_bauer @ACM_TORS @PLUS_1622 That's really cool! Congratulations :)

[Mohammad Aliannejadi @maliannejadi]

Are LLMs the end of IR? @ekanou presenting 42 things you need to know about IR at #ESSIR24.

[David Vos @dja_vos]

This is really cool stuff. Proud of these two guys, @Dafidofff and @davidmknigge! Go check out their work :)

[David Wessels @Dafidofff]

🥠 Excited to introduce our latest work on Equivariant Neural Fields (ENFs)! Grounding conditioning variables in geometry 🚀

Paper: https://t.co/LQONG1iQ2o
Github: https://t.co/yKXZBLDEJU
Project Page: https://t.co/lNpz11Z9Hi

Details below 👇👇

[David Vos @dja_vos]

Structured data is everywhere. Now we just need to unlock its potential!

A unique opportunity to go work with Madelon! And across the street from my office :)

[Mohammad Aliannejadi @maliannejadi]

📣📣 Check out ESSIR 2024's program!

We start with Transformers, Foundation Models, and Finetuning, followed by Generative IR, LLMs, (Neural) RecSys, LTR, Evaluation, Explainability, and Fairness.

ESSIR features FIDA and a week-long hackathon!

👩🏻‍💻 https://t.co/o7SUiOgwIy

[The IRLab at the University of Amsterdam @irlab_amsterdam]

SEA 🌊 is back! Join us on Friday, May 17th, when @olivierjeunen takes a critical look at evaluating recommender systems using nDCG!

Sign up here 👉: https://t.co/w9tHCdN4sq