iiinova — where your digital self keeps evolving

Uma Gunturi @umagunturi1.bsky.social · 05/10/2026

Attending #TADA2026 at UC Berkeley today! Catch me presenting our poster (#27) on counter-storytelling at 11:45 am in Krutch Auditorium! Our poster explores how people use personal stories on Reddit to challenge stereotypes. w @mariaa.bsky.social @maartensap.bsky.social @jiminmun.bsky.social

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Hiroki Sayama @hirokisayama.bsky.social · 29/07/2026

#IC2S2 keynote Gasper Begus giving a fascinating talk about analyzing languages spoken by whales @ic2s2.bsky.social

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Uma Gunturi @umagunturi1.bsky.social · 29/07/2026

In Burlington for #IC2S2! So excited to present our poster today on counter storytelling in racial counterpublics w @mariaa.bsky.social! If you're interested in narratives on social media - come say hi! Where to find us? 📅 Wed, July 29 🕜 1:15–2:15 PM 📍 Davis Center, Poster #13 @ic2s2.bsky.social

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Maria Antoniak @mariaa.bsky.social · 28/07/2026

I’m on my way to my first #IC2S2! 🌧️ I’ll be supporting presentations about computational narrative analysis by my students and mentees @teagrjohnson.bsky.social and @umagunturi1.bsky.social. If you’re interested in storytelling, pretraining data, social media, or language models, come talk to us!

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Denis @dpeskoff.bsky.social · 14/07/2026

Do you work across computational methods, social sciences, and the humanities? Submit to Text as Data 2026! 📄 One-page submissions 🔓 Non-archival ⏰ Due August 1 📍 October 5 @UCBerkeley tada2026.org

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Teagan Johnson @teagrjohnson.bsky.social · 19/06/2026

1/ LLMs learn narrative from their pretraining data but what narrative content is actually in there? It turns out narrative is wildly unevenly distributed across sources and topics. New preprint with @andrewpiper.bsky.social @elliottash.bsky.social @mariaa.bsky.social:

This image depicts the proportion of each Dolma category in the top quartile for the first three principal components.

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potatoannotator.bsky.social @potatoannotator.bsky.social · 29/01/2026

Super proud that today we're releasing Potato 2.0 - the biggest update yet to our open-source annotation platform www.potatoannotator.com 🥔 Major UI/UX improvements. Support for image, audio & video annotation. AI-powered assistance/hints/labeling. And still free 🤩 Here's some of what's new:

potatoannotator.com

Potato - AI-Powered Annotation Tool

From zero to annotating in minutes. Configuration-first annotation with AI features.

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Alexandra Olteanu @aolteanu.bsky.social · 05/12/2025

📣 It's again that time of the year 🤩 - our internship call for the FATE team @ MSR Montreal and our collaborators is now up! 🎉🎉 We are broadly looking for candidates interested in perceptions, evaluation, uses, and impacts of AI! #FAccT #FAccT2025 #CHI2025 #NeurIPS2025 #ACL2025

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Dan Goldstein @dggoldst.bsky.social · 05/12/2025

Want to be an intern at Microsoft Research in the Computational Social Science group in NYC (Jake Hofman, David Rothschild, Dan Goldstein) Follow this link and do your thing! Deadline approaching soonish! apply.careers.microsoft.com/careers/job/...

apply.careers.microsoft.com

Research Intern - Computational Social Science | Microsoft Careers

Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Researc...

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bhyravajjula.bsky.social @bhyravajjula.bsky.social · 31/10/2025

When you read a poem, do you wonder how the poet structures it through whitespace between/before words and lines? We did! Our findings on whitespace - how to measure/preserve it, how usage varies across form/time, how it affects LLMs - now in an #EMNLP2025 (main) paper: arxiv.org/abs/2510.16713 🧵👇

"so much depends / upon / a whitespace: Why Whitespace Matters for Poets and LLMs" by Sriharsh Bhyravajjula, Melanie Walsh, Anna Preus, Maria Antoniak

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Ramon Astudillo @ramon-astudillo.bsky.social · 07/10/2025

(repost welcome) The Generative Model Alignment team at IBM Research is looking for next summer interns! Two candidates for two topics 🍰Reinforcement Learning environments for LLMs 🐎Speculative and non-auto regressive generation for LLMs interested/curious? DM or email ramon.astudillo@ibm.com

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Jay 🦋 @jay.bsky.team · 01/10/2025

We’re hiring for two machine learning roles. A chance to do cutting edge things with ML to make this place a lot more personalized. jobs.gem.com/bluesky/am9i...

jobs.gem.com

Bluesky Jobs

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VL/HCC @vlhcc.bsky.social · 02/10/2025

See you at #VLHCC25 next week!

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Joel Mire @joelmire.bsky.social · 06/03/2025

Reward models for LMs are meant to align outputs with human preferences—but do they accidentally encode dialect biases? 🤔 Excited to share our paper on biases against African American Language in reward models, accepted to #NAACL2025 Findings! 🎉 Paper: arxiv.org/abs/2502.12858 (1/10)

Screenshot of Arxiv paper title, "Rejected Dialects: Biases Against African American Language in Reward Models," and author list: Joel Mire, Zubin Trivadi Aysola, Daniel Chechelnitsky, Nicholas Deas, Chrysoula Zerva, and Maarten Sap.

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Julia Mendelsohn @jmendelsohn2.bsky.social · 20/02/2025

New preprint! Metaphors shape how people understand politics, but measuring them (& their real-world effects) is hard. We develop a new method to measure metaphor & use it to study dehumanizing metaphor in 400K immigration tweets Link: bit.ly/4i3PGm3 #NLP #NLProc #polisky #polcom #compsocialsci 🐦🐦

Screenshot of top half of first page of paper. The paper is titled: "When People are Floods: Analyzing Dehumanizing Metaphors in Immigration Discourse with Large Language Models". The authors are Julia Mendelsohn (University of Chicago) and Ceren Budak (University of Michigan). The top right corner contains a visual showing the sentence "They want immigrants to pour into and infest this country". The caption says: Figure 1: Dehumanizing sentence likening immigrants to the source domain concepts of Water and Vermin via the words "pour" and "infest".

The abstract text on the left reads: Metaphor, discussing one concept in terms of another, is abundant in politics and can shape how people understand important issues. We develop a computational approach to measure metaphorical language, focusing on immigration discourse on social media. Grounded in qualitative social science research, we identify seven concepts evoked in immigration discourse (e.g. "water" or "vermin"). We propose and evaluate a novel technique that leverages both word-level and document-level signals to measure metaphor with respect to these concepts. We then study the relationship between metaphor, political ideology, and user engagement in 400K US tweets about immigration. While conservatives tend to use dehumanizing metaphors more than liberals, this effect varies widely across concepts. Moreover, creature-related metaphor is associated with more retweets, especially for liberal authors. Our work highlights the potential for computational methods to complement qualitative approaches in understanding subtle and implicit language in political discourse.

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Dan Jurafsky @jurafsky.bsky.social · 12/01/2025

Happy New Year everyone! Jim and I just put up our January 2025 release of Speech and Language Processing! Check it out here: web.stanford.edu/~jurafsky/sl...

web.stanford.edu

Speech and Language Processing

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Maria Antoniak @mariaa.bsky.social · 31/12/2024

It's ready! 💫 A new blog post in which I list of all the tools and apps I've been using for work, plus all my opinions about them. maria-antoniak.github.io/2024/12/30/o... Featuring @kagi.com, @warp.dev, @paperpile.bsky.social, @are.na, Fantastical, @obsidian.md, Claude, and more.

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