Katie Keith

Congratulations to our very own Dr. Tanise Ceron for successfully defending her PhD on "Methods for Mining Political Opinions from Texts & Language Models". 🥳 #NLProc #NLP Check out her amazing work here: tceron.github.io/publications/ @taniseceron 📚 #PhDDefense #AcademicResearch

@strubell @WilliamsCollege Haha great pick @strubell. I see you also hiked to Stoney Ledge:) s

Our @WilliamsCollege computer science department is hiring TWO TENURE-TRACK FACULTY this cycle: apply.interfolio.com/148956 (1/4)

These were some of the many reasons I chose Williams. No institution is perfect, but this one checks a lot of boxes. Hope you can join us! (4/4)

3. 5 out of 13 tenure-track CS faculty are women 4. Student body: 52% receive need-based financial aid (all grants) and over 40% identify as US students of color. (3/4)

Why Williams? 1. Strives for high teaching standards with 2-1 course load 2. Emphasis on quality research, evidenced by faculty grant success cfr.williams.edu/recent-externa… (3/4)

@emaadmanzoor Thanks @emaadmanzoor! Shout-out to my very sharp collaborators @r0ntu and Jacob Chen.

Love this paper by @katakeith, such a clever idea to control for text using proximal causal inference! arxiv.org/abs/2401.06687

@lbiester23 This looks like a fantastic resource Laura! I might use your beam search stuff in my NLP class this fall 🙏

The worksheets, which cover a number of topics, ensured that students understood the algorithm prior to starting their programming homework and helped with debugging. Paper: aclanthology.org/2024.teachingn… Resources (Worksheets + Programming Assignments): github.com/lbiester/Teach…

I am in Bangkok this week for #ACL2024NLP! I am organizing the @teaching_nlp workshop and also presenting a paper at the workshop, "Tightly Coupled Worksheets and Homework Assignments for NLP." The paper introduces paired HW assignments and worksheets from in my NLP class.

@umdcs @UofMaryland @MohitIyyer @gkaptchuk @HanShao16 Congrats @MohitIyyer !

.@UofMaryland's CS dept is welcoming eight new tenure-track faculty members! With expertise in cutting-edge areas, they'll boost our academic & research capabilities. Welcome aboard! 🐢📚 Read more: go.umd.edu/Hires24

I've reflected on this a bit "Annotator Uncertainty" portion of our earlier paper aclanthology.org/2020.nlpcss-1.…. Also whether we should use a soft loss function in this tutorial of mine #scrollTo=2cbyq8APXTWY" target="_blank" rel="nofollow noopener">colab.research.google.com/drive/1ulQSwlS….

At @nlpandcss, Naoki Egami “Using Large Language Model Annotations for the Social Sciences" talk, lots of questions about the assumptions of "annotators as ground truth." I think this is a really important question! Often disagreement is an inherently useful signal.

NLP+CSS workshop starting in minutes! Hope you can join us virtually or in person! @nlpandcss

I'm a bit biased 😀, but I found this a great read for those interested in text+causal inference!

We are only 5 days out of the @nlpandcss workshop and I am in-route to Mexico City 🇲🇽 #naacl2024! Excited for the invited talks from Naoki Egami, @hego_py, and @maria_antoniak, and learning from the rest of our accepted authors! Program: sites.google.com/site/nlpandcss…

@maria_antoniak @CUBoulder Congrats!!!!

In Fall 2025, I’ll be joining @CUBoulder’s CS Department! I’m so excited to join this group of researchers, students, and teachers in the beautiful Rocky Mountains ☀️ I’ll be recruiting students this fall to start in 2025, so please send applicants my way!

Exciting set of ideas and people coming from American Causal Inference Conference (ACIC) in Seattle this past week! Smaller conferences = more ideas sparked. Fantastic watching @r0ntu and my @WilliamsCollege undergraduate students share their work!

Rohit @r0ntu will also talk about the work during the New England Statistics Symposium on May 24 symposium.nestat.org/index.html

I will talk about this work at ACIC at 9am tomorrow (May 16) during the the invited session “Statistical innovations in causal inference with text as data: Emerging trends and future directions” sci-info.org/annual-meeting…

Excited for two upcoming opportunities where we’ll talk about our TMLR paper (which was published this fall) “RCT Rejection Sampling for Causal Estimation Evaluation” with coauthors @SergeyFeldman @david__jurgens @turingmusician @r0ntu openreview.net/pdf?id=F74ZZk5…