iiinova — where your digital self keeps evolving

Reposted by Ethan Gotlieb Wilcox

Xiulin Yang @xiulinyang.bsky.social · 28/08/2026

🍎🍊 How would you know if a language model is better at one language than another? Our #EMNLP2026 paper argues that only one metric can actually lead to fair crosslingual evaluation. This work is a collaboration with @wegotlieb.bsky.social & @catherinearnett.bsky.social! (1/5)

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/05/2026

This is a beautiful message, Gasper. Thanks for sharing!

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Reposted by Ethan Gotlieb Wilcox

Georgetown Linguistics @georgetownlingdept.bsky.social · 14/11/2025

Virtual information session for Georgetown’s 2-year Master’s in Computational Linguistics! Learn about our courses in NLP, psycholinguistics, low-resource languages, digital humanities, and LLMs, plus phonology, syntax, & semantics. DM for registration link. Friday Nov. 21 | 10–11 AM #linguistics

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Reposted by Ethan Gotlieb Wilcox

Jennifer Hu @jennhu.bsky.social · 10/11/2025

New work to appear @ TACL! Language models (LMs) are remarkably good at generating novel well-formed sentences, leading to claims that they have mastered grammar. Yet they often assign higher probability to ungrammatical strings than to grammatical strings. How can both things be true? 🧵👇

Screenshot of a figure with two panels, labeled (a) and (b). The caption reads: "Figure 1: (a) Illustration of messages (left) and strings (right) in toy domain. Blue = grammatical strings. Red = ungrammatical strings. (b) Surprisal (negative log probability) assigned to toy strings by GPT-2."

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 23/10/2025

I did not! Yikes! Another reason to include "pickle" and/or pickle-related emoji in any lab communication!

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 21/10/2025

Georgetown Linguistics has a dedicated Computational Linguistics PhD track, and a lively CL community on campus (gucl.georgetown.edu), including my faculty colleagues @complingy.bsky.social and Amir Zeldes.

gucl.georgetown.edu

GUCL: Computation and Language @ Georgetown

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 21/10/2025

PICoL stands for “Psycholinguistics, Information, and Computational Linguistics,” and I encourage applications from anyone whose research interests connect with these topics!

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 21/10/2025

I will be recruiting PhD students via Georgetown Linguistics this application cycle! Come join us in the PICoL (pronounced “pickle”) lab. We focus on psycholinguistics and cognitive modeling using LLMs. See the linked flyer for more details: bit.ly/3L3vcyA

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 03/06/2025

🌟🌟This paper will appear at ACL 2025 (@aclmeeting.bsky.social)! New updated version is on arXiv: arxiv.org/pdf/2505.07659 🌟🌟

arxiv.org

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Reposted by Ethan Gotlieb Wilcox

Sasha Boguraev @sashaboguraev.bsky.social · 27/05/2025

A key hypothesis in the history of linguistics is that different constructions share underlying structure. We take advantage of recent advances in mechanistic interpretability to test this hypothesis in Language Models. New work with @kmahowald.bsky.social and @cgpotts.bsky.social! 🧵👇!

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

We see this project as in line with some other recent papers seeking to cast typological variation in information-theoretic terms, with shout-outs to Michaela Socolof, @postylem.bsky.social @futrell.bsky.social (aclanthology.org/2022.coling-...) and Julius Steuer (aclanthology.org/2023.sigtyp-...)

aclanthology.org

Measuring Morphological Fusion Using Partial Information Decomposition

Michaela Socolof, Jacob Louis Hoover, Richard Futrell, Alessandro Sordoni, Timothy J. O’Donnell. Proceedings of the 29th International Conference on Computational Linguistics. 2022.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

⭐ ⭐This paper also makes several technical contributions to the mixed-pair mutual information estimation pipeline of Wolf et al., (aclanthology.org/2023.emnlp-m...). Shout out to @cuiding.bsky.social for all her hard work on this aspect of the paper! ⭐⭐

aclanthology.org

Quantifying the redundancy between prosody and text

Lukas Wolf, Tiago Pimentel, Evelina Fedorenko, Ryan Cotterell, Alex Warstadt, Ethan Wilcox, Tamar Regev. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

✅In line with our prediction, we find that mutual information is higher in tonal languages than in non-tonal languages. BUT, the way one represents context is important. When full sentential context is taken into account (mBERT and mGPT), the distinction collapses.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

🌏🌍We test this prediction by estimating mutual information in an audio dataset of 10 different languages across 6 language families. 🌏🌍

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

We propose a way to do so using …📡information theory.📡 In tonal languages, pitch reduces uncertainty about lexical identity, therefore, the mutual information between pitch and words should be higher.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

🌐But there are intermediate languages, which have lexically contrastive tone, but only sporadically, making some linguists doubt the tonal/non-tonal dichotomy. So, how can we measure how “tonal” a language is? 🧐🧐

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 13/05/2025

🌏 Different languages use pitch in different ways. 🌏 “Tonal” languages, like Cantonese, use it to make lexical distinctions. 📖 While others, like English, use it for other functions, like marking whether or not a sentence is a question. ❓

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 12/05/2025

I’ll also use this as a way to plug human-scale language modeling in the wild: This year’s BabyLM eval pipeline was just released last week at github.com/babylm/evalu.... For more info on BabyLM head to babylm.github.io

github.com

GitHub - babylm/evaluation-pipeline-2025

Contribute to babylm/evaluation-pipeline-2025 development by creating an account on GitHub.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 12/05/2025

Couldn’t be happier to have co-authored this will a stellar team, including: Michael Hu, @amuuueller.bsky.social, @alexwarstadt.bsky.social, @lchoshen.bsky.social, Chengxu Zhuang, @adinawilliams.bsky.social, Ryan Cotterell, @tallinzen.bsky.social

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 12/05/2025

This version includes 😱New analyses 😱new arguments 😱 and a whole new “Looking Forward” section! If you’re interested in what a team of (psycho) computational linguists thinks the future will hold, check out our brand new Section 8!

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 12/05/2025

📣Paper Update 📣It’s bigger! It’s better! Even if the language models aren’t. 🤖New version of “Bigger is not always Better: The importance of human-scale language modeling for psycholinguistics” osf.io/preprints/ps...

osf.io

OSF

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Reposted by Ethan Gotlieb Wilcox

Cui Ding @cuiding.bsky.social · 07/03/2025

Excited to share our preprint "Using MoTR to probe agreement errors in Russian"! w/ Metehan Oğuz, @wegotlieb.bsky.social, Zuzanna Fuchs Link: osf.io/preprints/ps... 1- We provide moderate evidence that processing of agreement errors is modulated by agreement type (internal vs external agr.)

osf.io

OSF

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Reposted by Ethan Gotlieb Wilcox

John Mansfield @johnbasil.bsky.social · 27/02/2025

Me and @wegotlieb.bsky.social were recently invited to write a wide-ranging reflection on the current state of linguistic theory and methodology. A draft is up here. For anyone interested in thinking big about linguistics, we'd be happy to hear your thoughts! arxiv.org/abs/2502.18313 #linguistics

arxiv.org

Looking forward: Linguistic theory and methods

This chapter examines current developments in linguistic theory and methods, focusing on the increasing integration of computational, cognitive, and evolutionary perspectives. We highlight four major ...

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/02/2025

⚖️📣This paper was a big departure from my typical cognitive science fare, and so much fun to write! 📣⚖️ Thank you to @bwal.bsky.social and especially to @kevintobia.bsky.social for their legal expertise on this project!

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/02/2025

On the positive side, we suggest that LLMs can serve a role as “dialectic” partners 🗣️❔🗣️ helping judges and clerks strengthen their arguments, as long as judicial sovereignty is maintained 👩‍⚖️👑👩‍⚖️

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/02/2025

⚖️ We also show, through demonstration, that it’s very easy to engineer prompts that steer models toward one’s desired interpretation of a word or phrase. 📖Prompting is the new “dictionary shopping” 😬 📖 😬

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/02/2025

🏛️We identify five “myths” about LLMs which, when dispelled, reveal their limitations as legal tools for textual interpretation. To take one example, during instruction tuning, LLMs are trained on highly structured, non-natural inputs.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/02/2025

We argue no! 🙅‍♂️ While LLMs appear to possess excellent language capabilities, they should not be used as references for “ordinary language use,” at least in the legal setting. ⚖️ The reasons are manifold.

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Ethan Gotlieb Wilcox @wegotlieb.bsky.social · 19/02/2025

🏛️Last year a U.S. judge queried Chat GPT to help with their interpretation of “ordinary meaning,” in the same way one might use a dictionary to look up the ordinary definition of a word 📖 … But is it the same?

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