David Mueller

ML/NLP PhD candidate @jhuclsp
focused on multi-task and multi-lingual learning.
he/him

mastodon: @[email protected]

[Marc Marone @ ICML 2026 @ruyimarone]

Presenting my poster on dataset documentation today at 5pm (#619)!

If you liked Jelani Nelson's keynote yesterday on sketching, come see how we use efficient datastructures to document datasets at crazy compression: 800 GB dataset ➡️ 27 GB 🎉🎉🎉

[Tianjian Li @tli104]

I have written a blogpost on balancing multiple directions in multilingual translation, which covers some of the latest advances in #NeurIPS2023.

Link: https://t.co/pLa6asT1u9

[Drew Prinster @DrewPrinster]

Can I trust this AI/ML prediction? A good uncertainty quantification (UQ) method could answer this with a predictive confidence interval. But in practice, 2 key challenges limit real-world UQ.

Our #ICML2023 Oral “JAWS-X” tackles these challenges! 🧵w/ @suchisaria @anqi_liu33 1/n

[Jing Yu Koh @kohjingyu]

The competition gets stiffer every year

[Tiffany Vlaar @TiffanyVlaar]

Call for reviewers for our #ICLR2023 workshop on Mathematical and Empirical Understanding of Foundation Models.

Fill out this form if you are interested
https://t.co/ItY41LqQpU
and we will aim to get back to you asap.

Paper deadline: 3 Feb
Tentative reviewing period: 10-24 Feb.

[Gabriel Ilharco @gabriel_ilharco]

Introducing task vectors!

A new way to steer models by doing arithmetic with model weights. Subtract to make models forget, add to make them learn

📜: https://t.co/YNQvdYtdSN
🖥️: https://t.co/CVFM68u322

[Mark Dredze @mdredze]

I want to talk about our #EMNLP2022 paper, led by @dam_nlp with Nick Andrews.

Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?

https://t.co/Ln0xctnFG4

We've got some pretty interesting analyses for those working in multi-task language model training.

[Amin Karbasi @aminkarbasi]

High-Dimensional Probability https://t.co/mmeYW4Le9C

[Yunmo Chen @YunmoChen]

Our #EMNLP2022 paper compares the effectiveness of three span finding methods for information extraction tasks: Tagging, Span Enumeration, and Boundary Prediction. See the full paper here: https://t.co/z9pa9PSP0m (w/ Weiwei Gu, @Boyuan62136063, @ctongfei, @ben_vandurme)🧵1/6

[Greg Durrett @gregd_nlp]

Come see our presentations at EMNLP!
https://t.co/RUODKdz1wf
All of these papers represent directions in textual reasoning and summarization that have been in the works for a while and I'm excited that we're finally sharing them! Up tomorrow: @tanyaagoyal and @ZayneSprague

[Anqi (Angie) Liu @anqi_liu33]

Given I am lucky enough to be at #NeurIPS2022 in person, I am proud to present our poster on collecting and learning from ambiguous images and human uncertainties this afternoon Hall J #1002. This is a joint work with amazing collaborators @kesnet50 @ben_vandurme and Reno Kriz.

[David Mueller @dam_nlp]

@EliasEskin Semantic Santa, is that you?

[Michael Zhang @michaelrzhang]

#NeurIPS2022 group run 8am starting from Lafayette Square tomorrow (Thursday), everyone is welcome!

We plan to run north along the river (passing through French Quarter)

[David Mueller @dam_nlp]

@GRESEARCHjobs Thank u 🤗

[David Mueller @dam_nlp]

Important #NeurIPS2022 question: does @GRESEARCHjobs have a barista, and if not where do I find yummy coffee?

[Drew Prinster @DrewPrinster]

If you’re at #NeurIPS2022 come see our poster Hall J #941 TODAY (11/29) 4-6pm!

With @anqi_liu33 @suchisaria, we present “JAWS: Auditing Predictive Uncertainty Under Covariate Shift”

Virtual talk: https://t.co/SisRJ0sn1A
Paper: https://t.co/nysFRP3de8

[Sara Hooker @sarahookr]

What is a work boat?

[Carlos Aguirre Pocasangre @pocaguirre]

Yes! Come check my poster during session 2 @SymposiumML4H (4:40pm)

[David Mueller @dam_nlp]

@rdesh26 Optimistically or realistically? ;)

[Sara Hooker @sarahookr]

Is there anyone attending NeurIPS who is a leader at a funding body such as NSF, CIFAR or [[insert here other national or supranational funding body]]?

I'm moderating a panel for NeurIPS on "How has funding and incentive structures impacted the history of computer science?"