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Lindia Tjuatja

@lindiatjuatja.bsky.social
2.1K followers 437 following 57 posts

a natural language processor and “sensible linguist”. PhD-ing LTI CMU, incoming asst. prof. @ UT linguistics (F27)! 🤠🤖📖 she/her lindiatjuatja.github.io

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Reposted by Lindia Tjuatja
Jessy Li @jessyjli.bsky.social · 30/06/2026
I will miss #ACL2026 this year, but check out work from my students and collaborators! Kaijie (@kaijie-mo.bsky.social), Sebastian (@sebajoe.bsky.social), Asher (@asher-zheng.bsky.social), Lily, and Gauri will be there presenting the following: jessyli.com/acl2026
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Kanishka Misra @kanishka.bsky.social · 29/06/2026
I will be at #ACL2026 from July 2--7! I will be giving a keynote at CDL workshop on controlled rearing and hypothesis generation from language models! Tianyang Xu (first author) and I will present work on cross-modal generalization in VLMs on July 7! Paper: aclanthology.org/2026.acl-lon...
low effort slide on my activities during ACL.

Keynote at computational developmental linguistics workship (July 4, 3pm)

Poster w/ Tianyang Xu during Poster session G (July 7, 11-12)

Recruiting for my lab @ full conference!
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Lindia Tjuatja @lindiatjuatja.bsky.social · 30/06/2026
I will be at #ACL2026 from July 2-7! Along with checking out the conference and hanging around SD, I'm also ✨recruiting students for Fall 2027 @ UT Austin Linguistics (along with @kanishka.bsky.social )✨ Some topics I'm really excited about below ⬇️
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Lindia Tjuatja @lindiatjuatja.bsky.social · 06/04/2026
Really excited about this work w/ my long-time collaborators at Boulder! We address limitations in existing morphosyntactic annotation systems for digitally under-resourced languages and show how *jointly* predicting morphological segmentation helps with glossing performance
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Michael Saxon @saxon.me · 18/10/2025
The viral "Definition of AGI" paper tells you to read fake references which do not exist! Proof: different articles present at the specified journal/volume/page number, and their titles exist nowhere on any searchable repository. Take this as a warning to not use LMs to generate your references!
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Aaron Steven White @aaronstevenwhite.io · 27/09/2025
I've found it kind of a pain to work with resources like VerbNet, FrameNet, PropBank (frame files), and WordNet using existing tools. Maybe you have too. Here's a little package that handles data management, loading, and cross-referencing via either a CLI or a python API.
github.com
GitHub - aaronstevenwhite/glazing: Unified data models and interfaces for syntactic and semantic frame ontologies.
Unified data models and interfaces for syntactic and semantic frame ontologies. - aaronstevenwhite/glazing
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Hadas Kotek 🦄 @hadaskotek.bsky.social · 08/08/2025
Good news (for me!) my gender bias paper from 2023 still replicates with GPT-5. Bad news (for everyone!) my gender bias paper from 2023 still replicates with GPT-5. arxiv.org/pdf/2308.14921 hkotek.com/blog/gender-...
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Lindia Tjuatja @lindiatjuatja.bsky.social · 25/07/2025
🇦🇹I'll be at #ACL2025! Recently I've been thinking about: ✨linguistically + cognitively-motivated evals (as always!) ✨understanding multilingualism + representation learning (new!) I'll also be presenting a poster for BehaviorBox on Wed @ Poster Session 4 (Hall 4/5, 10-11:30)!
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Emma Strubell @strubell.bsky.social · 14/07/2025
I did an interview w/ Pittsburgh's NPR station to share some of my views on the topic of the McCormick/Trump AI & Energy summit at CMU tomorrow. Despite being hosted at the university, there will not be opportunities for our university experts to contribute viewpoints at the event.
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Alexandra Olteanu @aolteanu.bsky.social · 18/06/2025
We have to talk about rigor in AI work and what it should entail. The reality is that impoverished notions of rigor do not only lead to some one-off undesirable outcomes but can have a deeply formative impact on the scientific integrity and quality of both AI research and practice 1/
Print screen of the first page of a paper pre-print titled "Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor" by Olteanu et al.  Paper abstract: "In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI community, including overblown claims about AI capabilities. Our position is that a broader conception of what rigorous AI research and practice should entail is needed. We believe such a conception -- in addition to a more expansive understanding of (1) methodological rigor -- should include aspects related to (2) what background knowledge informs what to work on (epistemic rigor); (3) how disciplinary, community, or personal norms, standards, or beliefs influence the work (normative rigor); (4) how clearly articulated the theoretical constructs under use are (conceptual rigor); (5) what is reported and how (reporting rigor); and (6) how well-supported the inferences from existing evidence are (interpretative rigor). In doing so, we also aim to provide useful language and a framework for much-needed dialogue about the AI community's work by researchers, policymakers, journalists, and other stakeholders."
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Graham Neubig @gneubig.bsky.social · 09/06/2025
Where does one language model outperform the other? We examine this from first principles, performing unsupervised discovery of "abilities" that one model has and the other does not. Results show interesting differences between model classes, sizes and pre-/post-training.
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Lindia Tjuatja @lindiatjuatja.bsky.social · 09/06/2025
When it comes to text prediction, where does one LM outperform another? If you've ever worked on LM evals, you know this question is a lot more complex than it seems. In our new #acl2025 paper, we developed a method to find fine-grained differences between LMs: 🧵1/9
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Lindia Tjuatja @lindiatjuatja.bsky.social · 30/04/2025
Hanging around NAACL and presenting this Thurs, 4:15 @ ling theories oral session (ballroom 🅱️). Come say hi, will also be eating many a sopapilla
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Ted Underwood @tedunderwood.com · 23/01/2025
I wasn’t super excited by o1, but as reasoning models go open-weights I’m starting to see how they make this interesting again. The 2022-24 “just scale up” period was both very effective and very boring.
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Lindia Tjuatja @lindiatjuatja.bsky.social · 22/01/2025
Accept to NAACL main! See yall in NM ☀️
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Lindia Tjuatja @lindiatjuatja.bsky.social · 31/12/2024
cat
sleeping orange catorange cat getting petsalert orange cat
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Lindia Tjuatja @lindiatjuatja.bsky.social · 29/12/2024
I am once again asking for {cafe, food, work spots, things to see and do} for a place I will be visiting: the baaaay 🌁 (My first time visiting NorCal *ever* so the regular tourist spots are welcome!)
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Joey Stanley @joeystanley.com · 18/12/2024
I don't remember who created this, where I got it from, or how long I've had it, but I have it on my slides as students walk in the first time we talk about Labov's NYC study. And it makes me chuckle every time I see it for some reason. "Very rhotic. Very stratified." 😆
The movie poster for "Love Actually" but changed to "Labov Actually" with his face pasted over everyone else's and fun changes throughout like "very romantic, very comedy" changed to "very rhotic, very stratified."
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Sireesh Gururaja @siree.sh · 17/12/2024
When I started on ARL project that funds my PhD, the thing we were supposed to build was a "MaterialsGPT". What is a MaterialsGPT? Where does that idea come from? I got to spend a lot of time thinking about that second question with @davidthewid.bsky.social and Lucy Suchman (!) working on this:
The abstract of a paper titled "Basic Research, Lethal Effects: Military AI Research Funding as Enlistment".

In the context of unprecedented U.S. Department of Defense (DoD) budgets, this paper examines the recent history of DoD funding for academic research in algorithmically based warfighting. We draw from a corpus of DoD grant solicitations from 2007 to 2023, focusing on those addressed to researchers in the field of artificial intelligence (AI). Considering the implications of DoD funding for academic research, the paper proceeds through three analytic sections. In the first, we offer a critical examination of the distinction between basic and applied research, showing how funding calls framed as basic research nonetheless enlist researchers in a war fighting agenda. In the second, we offer a diachronic analysis of the corpus, showing how a 'one small problem' caveat, in which affirmation of progress in military technologies is qualified by acknowledgement of outstanding problems, becomes justification for additional investments in research. We close with an analysis of DoD aspirations based on a subset of Defense Advanced Research Projects Agency (DARPA) grant solicitations for the use of AI in battlefield applications. Taken together, we argue that grant solicitations work as a vehicle for the mutual enlistment of DoD funding agencies and the academic AI research community in setting research agendas. The trope of basic research in this context offers shelter from significant moral questions that military applications of one's research would raise, by obscuring the connections that implicate researchers in U.S. militarism.
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Lindia Tjuatja @lindiatjuatja.bsky.social · 17/12/2024
got a new suitcase but the main beneficiary of this purchase was my cat
My orange cat checking out a large cardboard boxMy orange cat looking back at me from within a large cardboard boxMy orange cat appreciating the height of a large cardboard box she is in
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Lindia Tjuatja @lindiatjuatja.bsky.social · 04/12/2024
I always think classical music is great to work to, and then I put on something a little too emotional, and then I’m just left sitting motionless and staring at my screen
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Lindia Tjuatja @lindiatjuatja.bsky.social · 02/12/2024
anyone have recs for good coffee shops to work from in nyc / working spaces in general? around nyu is a plus!
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Lindia Tjuatja @lindiatjuatja.bsky.social · 27/11/2024
this is incredible
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Lindia Tjuatja @lindiatjuatja.bsky.social · 26/11/2024
I love it when my reviewers read my paper.
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Leonie Weissweiler @weissweiler.bsky.social · 26/11/2024
@kanishka.bsky.social and I have made a starter pack for researchers working broadly on linguistic interpretability and LLMs! go.bsky.app/F9qzAUn Please message me or comment on this post if you've noticed someone who we forgot or would like to be added yourself!
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Kirby Conrod @kirbyconrod.bsky.social · 26/11/2024
Just got an email from the zombie journal soliciting my submissions so I thought I'd remind everyone that in 2015 the entire editorial board of "Lingua" resigned and created a new independent OA journal (Glossa). Don't submit to the new Lingua. slate.com/human-intere...
slate.com
Why the Editors of a Top Linguistic Journal Resigned En Masse
This post originally appeared on Inside Higher Ed.
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Brett Karlan @oldjerryfodor.bsky.social · 24/11/2024
"And what is it that LLMs need?" (someone from the audience) "Regulatory oversight!!" (someone else from the audience) "Democratization or elimination!!" "That's right, they need... a language of thought. Hi kids, my name is Jerry A. Fodor..."
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Catherine Arnett @catherinearnett.bsky.social · 22/11/2024
✨New pre-print!✨ Successful language technologies should work for a wide variety of languages. But some languages have systematically worse performance than others. In this paper we ask whether performance differences are due to morphological typology. Spoiler: I don’t think so! #NLP #linguistics
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Anna Rogers @annarogers.bsky.social · 22/11/2024
📢 NAACL reviews have been released! 🆕 feature alert: ARR now has review issue flagging! Thanks @jkkummerfeld.bsky.social & OR team for help with implementation, and other EiCs for supporting the idea! It'll be live after author response. More details here: aclrollingreview.org/authors#step... /1
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Lindia Tjuatja @lindiatjuatja.bsky.social · 20/11/2024
💬 Have you or a loved one compared LM probabilities to human linguistic acceptability judgments? You may be overcompensating for the effect of frequency and length! 🌟 In our new paper, we rethink how we should be controlling for these factors 🧵:
Screenshot of the paper title "What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Length"
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Lindia Tjuatja @lindiatjuatja.bsky.social · 18/11/2024
had a great time meeting old n new friends in Miami @ EMNLP! if {you stopped at my poster, I stopped at your poster, we had a hallway chat, we met over beverages} feel free to reach out to chat online as well :D
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Lindia Tjuatja @lindiatjuatja.bsky.social · 16/11/2024
It really was!!!
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michael ginn @mginn.bsky.social · 12/11/2024
Don’t forget to come check out the hottest new thing in interlinear glossing @ EMNLP, Tuesday 2-3:30
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Lindia Tjuatja @lindiatjuatja.bsky.social · 08/11/2024
(Hehe first bsky post!) I'll be at #EMNLP2024 💃🌴! Happy to chat about (among other things): ✨linguistically+cognitively motivated evaluation ✨NLP for low-resource+endangered languages ✨figuring out what features of language data LMs are *actually* learning I'll be presenting two posters 🧵:
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