iiinova — where your digital self keeps evolving

Reposted by Joel Mire

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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Reposted by Joel Mire

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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Reposted by Joel Mire

Aarthi Vadde @aarthivadde.bsky.social · 01/04/2026

We the Platform is available for preorder with the discount code CUP20 if you order directly from the press! cup.columbia.edu/book/we-the-... A thread on the argument below:

cup.columbia.edu

We the Platform | Columbia University Press

Web 2.0 gave us the online world as we know it today. Popularized in 2004, it redefined the internet as social, a “platform” for self-expression and data... | CUP

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Dr. Jordan Taylor @jordant.bsky.social · 10/03/2026

🎨💻 What is a “high-quality” or “aesthetic” image according to generative AI developers? Happy to share that our investigation of the LAION-Aesthetics Predictor has been accepted at #FAccT2026! 🧵 (1/5) Take a look at a preprint here: arxiv.org/abs/2601.09896

Screenshot of an academic paper titled "The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictor" authored by Jordan Taylor, William Agnew, Maarten Sap, Sarah E. Fox, and Haiyi Zhu

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Shaily @shaily99.bsky.social · 02/02/2026

🎭 How do LLMs (mis)represent culture? 🧮 How often? 🧠 Misrepresentations = missing knowledge? spoiler: NO! At #CHI2026 we are bringing ✨TALES✨ a participatory evaluation of cultural (mis)reps & knowledge in multilingual LLM-stories for India 📜 arxiv.org/abs/2511.21322 1/10

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Maarten Sap @maartensap.bsky.social · 02/02/2026

🚀 Apply to CMU LTI’s Summer 2026 “Language Technology for All” internship! 🎓 Open to pre‑doctoral students new to language tech (non‑CS backgrounds welcome). 🔬 12–14 weeks in‑person in Pittsburgh — travel + stipend paid. 💸 Deadline: Feb 20, 11:59pm ET. Apply → forms.gle/cUu8g6wb27Hs...

forms.gle

CMU LTI Summer 2026 Internship Program Application

We are looking for applicants for the Carnegie Mellon University Language Technology Institute's Summer 2026 "Language Technology for All" internship program. The main goal of this internship is to pr...

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Joel Mire @joelmire.bsky.social · 19/12/2025

Reading social media stories evokes a wide range of contextual reader reactions—inferential, affective, evaluative—yet we lack methods to study these at scale. Excited to share our new paper that builds a framework for analyzing storytelling practices across online communities!

Screenshot of paper title and authors.

Title: Social Story Frames: Contextual Reasoning about Narrative Intent and Reception
Authors: Joel Mire, Maria Antoniak, Steven R. Wilson, Zexin Ma, Achyutarama R. Ganti, Andrew Piper, Maarten Sap

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Reposted by Joel Mire

Lucy Li @lucy3.bsky.social · 11/11/2025

It's the season for PhD apps!! 🥧 🦃 ☃️ ❄️ Apply to Wisconsin CS to research - Societal impact of AI - NLP ←→ CSS and cultural analytics - Computational sociolinguistics - Human-AI interaction - Culturally competent and inclusive NLP with me! lucy3.github.io/prospective-...

A staircase in the new School of Computer, Data & Information Sciences building at Wisconsin Madison. Tan wood structures surround tapestry art and a small indoor garden.

A view from above of the staircases in the Wisconsin CDIS building

An shot from below of winding wooden staircases and a glass atrium rooftop. The new School of Computer, Data & Information Sciences building at Wisconsin Madison.

A bicolor white cat with seal-colored markings, looking upwards with big wide dark eyes.

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Reposted by Joel Mire

Amanda Bertsch @abertsch.bsky.social · 07/11/2025

Can LLMs accurately aggregate information over long, information-dense texts? Not yet… We introduce Oolong, a dataset of simple-to-verify information aggregation questions over long inputs. No model achieves >50% accuracy at 128K on Oolong!

Performance of a sweep of models on Oolong-synth and Oolong-real. Performance decreases with increasing context length, sometimes steeply.

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Reposted by Joel Mire

Kristina Gligoric @IC2S2 @gligoric.bsky.social · 05/11/2025

I'm recruiting multiple PhD students for Fall 2026 in Computer Science at @hopkinsengineer.bsky.social 🍂 Apply to work on AI for social sciences/human behavior, social NLP, and LLMs for real-world applied domains you're passionate about! Learn more at kristinagligoric.com & help spread the word!

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Mingqian Zheng @mingqian-zheng.bsky.social · 20/10/2025

How and when should LLM guardrails be deployed to balance safety and user experience? Our #EMNLP2025 paper reveals that crafting thoughtful refusals rather than detecting intent is the key to human-centered AI safety. 📄 arxiv.org/abs/2506.00195 🧵[1/9]

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Nina Beguš @ninabegus.bsky.social · 27/09/2025

10 years after the initial idea, Artificial Humanities is here! Thanks so much to all who have preordered it. I hope you enjoy reading it and find this research approach as generative as I do. More to come!

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Dr. Jordan Taylor @jordant.bsky.social · 14/05/2025

🏳️‍🌈🎨💻📢 Happy to share our workshop study on queer artists’ experiences critically engaging with GenAI Looking forward to presenting this work at #FAccT2025 and you can read a pre-print here: arxiv.org/abs/2503.09805

Academic paper titled un-straightening generative ai: how queer artists surface and challenge the normativity of generative ai models

The piece is written by Jordan Taylor, Joel Mire, Franchesca Spektor, Alicia DeVrio, Maarten Sap, Haiyi Zhu, and Sarah Fox.

As an image titled 24 attempts at intimacy showing 24 ai generated images with the word intimacy, none of which seems to include same gender couples

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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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Shaily @shaily99.bsky.social · 10/06/2025

🖋️ Curious how writing differs across (research) cultures? 🚩 Tired of “cultural” evals that don't consult people? We engaged with interdisciplinary researchers to identify & measure ✨cultural norms✨in scientific writing, and show that❗LLMs flatten them❗ 📜 arxiv.org/abs/2506.00784 [1/11]

An overview of the work “Research Borderlands: Analysing Writing Across Research Cultures” by Shaily Bhatt, Tal August, and Maria Antoniak. The overview describes that We survey and interview interdisciplinary researchers (§3) to develop a framework of writing norms that vary across research cultures (§4) and operationalise them using computational metrics (§5). We then use this evaluation suite for two large-scale quantitative analyses: (a) surfacing variations in writing across 11 communities (§6); (b) evaluating the cultural competence of LLMs when adapting writing from one community to another (§7).

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Saumya Malik @saumyamalik.bsky.social · 03/06/2025

I’m thrilled to share RewardBench 2 📊— We created a new multi-domain reward model evaluation that is substantially harder than RewardBench, we trained and released 70 reward models, and we gained insights about reward modeling benchmarks and downstream performance!

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Lucy Li @lucy3.bsky.social · 05/05/2025

I'm joining Wisconsin CS as an assistant professor in fall 2026!! There, I'll continue working on language models, computational social science, & responsible AI. 🌲🧀🚣🏻‍♀️ Apply to be my PhD student! Before then, I'll postdoc for a year in the NLP group at another UW 🏔️ in the Pacific Northwest

Wisconsin-Madison's tree-filled campus, next to a big shiny lake

A computer render of the interior of the new computer science, information science, and statistics building. A staircase crosses an open atrium with visibility across multiple floors

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Xuhui Zhou @nlpxuhui.bsky.social · 28/04/2025

When interacting with ChatGPT, have you wondered if they would ever "lie" to you? We found that under pressure, LLMs often choose deception. Our new #NAACL2025 paper, "AI-LIEDAR ," reveals models were truthful less than 50% of the time when faced with utility-truthfulness conflicts! 🤯 1/

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Maria Antoniak @mariaa.bsky.social · 15/04/2025

I updated our 🔭StorySeeker demo. Aimed at beginners, it briefly walks through loading our model from Hugging Face, loading your own text dataset, predicting whether each text contains a story, and topic modeling and exploring the results. Runs in your browser, no installation needed! ↳

A bar plot comparing the storytelling rates for different topics in the example dataset of congressional speeches. There are often large differences between storytelling and non-storytelling for individual topics. For example, the topic whose top words read "NUM, years, service, great, state" has much more storytelling that non-storytelling.

The top five congressional speeches for the topic "NUM, years, service, great state." All of the documents honor the lives of important people.

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Maria Antoniak @mariaa.bsky.social · 07/04/2025

New work on multimodal framing! 💫 Some fun results: comparisons of the same frame when expressed in images vs texts. When the "crime" frame is expressed in the article text, there are more political words in the text, but when the frame is expressed in the article image, more police words.

Table 2 from the paper, showing results of the "Fightin' Words" algorithm to rank words by their association with image vs text frames. Results are shown for the "crime" and "quality of life" frames.

Figure 13 from the paper showing scatter plots of the topic space (UMAP reduction of a 5k sample of the generated topic descriptions) with points highlighted if they were assigned the "political frame." The two plots display quite different distributions.

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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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