Alexander Hoyle @miserlis_
Postdoctoral fellow with @ETH_AI_Center. CSS + NLP. Previously CS PhD @umdcs, intern at @msftresearch and @ai2_allennlp. alexanderhoyle.com Joined May 2011-
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Alexander Hoyle retweeted
Want to do a 𝐩𝐨𝐬𝐭𝐝𝐨𝐜 in my group at 𝐄𝐓𝐇 𝐙𝐮𝐫𝐢𝐜𝐡? Check out our new position on "Multimodal reasoning models for oncology" which is centered around a new collab between our lab and kaiko . ai In addition, our group is engaged with the ETH AI Center and SwissAI projects where we have access to large-scale GPU ressources. Links in comment.
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@nsaphra i get these for you and literally only you. what is your secret
@AzmineWasi We really need to empower someone (ACs?) to desk-reject obviously bad papers and stop wasting people's time
@sebschu Thanks for your advice—it was obviously helpful :)
Delighted to announce the next step in my career! After my postdoc, I will begin a joint appointment at TU Wien and the Complexity Science Hub Vienna as an Assistant Professor in NLP! My deepest thanks to all who helped me along the way I'm hiring—details on PhD positions below
If you were considering schools in the US but are having visa issues/concerns about relocating there, please consider applying—of course Americans looking for outside opportunities are also welcome!
Why join? Vienna has a vibrant, rapidly-growing AI scene and a terrific quality of life; TU Wien has an excellent CS department; the Complexity Science Hub is a home to ambitious interdisciplinary work. If you are curious, opinionated, driven: come!
@NishantBalepur @rachelrudinger Wow, this is very fun. Nice work as usual !
We view this effort as a first rung on a reproducibility ladder, eventually ending with wholesale replication from only a research question Ben, and the rest of the team, did terrific work on this and I’m really excited for what’s next! Now on arXiv: arxiv.org/abs/2604.21965
New preprint out! Recent work tasks LLM agents with re-running existing social science replication code. Given current capabilities, that should be table stakes Here, we move up a level of abstraction, and ask models to reproduce results from a paper’s descriptions alone
Can AI agents read a social science paper and write the code from scratch to reproduce its results? No access to original code. Just text + data. New paper with Ben Kohler, @david_rzs, @__jae_1, and @miserlis_ 👇
Thanks for mavhing me! I had a lovely time!
We were thrilled to host @miserlis_ at our lab! His insightful talk on topic modeling sparked great discussions and fresh perspectives across the team. Thanks for the visit, we hope to welcome you back soon! #NLProc
Out of the whole space of bad LLM applications, there is something about this specifically that upsets me on a different level, because it so fundamentally misunderstands the thing it is trying to replace that I fail to understand how the idea ever arose in the first place.
@besttrousers @FuckoBucko1 @FamilyOfficeCA as much as one can be said to "agree" with a factual statement about causal graphs
@besttrousers @FuckoBucko1 @FamilyOfficeCA factcheck.org/2012/06/obamas… I remember this specifically because I found it so irksome (disclaimer: I am not a chud and agree with your original point)
@RexDouglass Could you elaborate/do you have some examples? I'm now sitting in an Econ group and I feel that CS research could benefit a lot from a similar emphasis on robustness/rigor/causality (although I agree both engage in a willful ignorance of existing work) doomscrollingbabel.manoel.xyz/p/the-missing-…
@causalinf I think you might be interested in our paper on LLMs for scalar measurement: aclanthology.org/2025.emnlp-mai…
@AaronSchein The closest you'd get to that with this approach is using slides.com
I wrote a blog post on my experience using AI for slide generation Basic idea: write your lecture notes first, then prompt the LLM to produce corresponding slides in reveal.js (h/t @ChenhaoTan). I'm picky about my slides but was happy with the results! (link in thread below)
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