In our new preprint, we explain how some salient features of representational geometry in language modeling originate from a single principle - translation symmetry in the statistics of data.
https://t.co/UPgLZTJ7i6
With @dhruvakarkada, @DanKorchinski, Andres Nava, and @MatthieuWyart.
There were hallucinated references at #NeurIPS2025 & @iclr_conf this year, so I built harcx https://t.co/GDi8brDvad.
A Python package to verify BibTeX citations against real academic databases. It supports papers, books, and
URLs.
Usage:
pip install harcx
harcx references.bib
Dissatisfied with EACL paper decisions? Fret not and submit your paper with ARR reviews to Multilingual Multicultural Evaluation workshop at EACL (both archival or nonarchival) until January 5th. 🔍🙂
https://t.co/9jHwS61B6d
1/ 🌍 How does mixing data from hundreds of languages affect LLM training?
In our new paper "Revisiting Multilingual Data Mixtures in Language Model Pretraining" we revisit core assumptions about multilinguality using 1.1B-3B models trained on up to 400 languages.
🧵👇
🚀The first-ever parametric LLM Unlearning Benchmark!
We find current unlearning only modify model’s behavior without truly erasing encoded knowledge in parameters, presenting ConceptVectors Benchmark, with each vector strongly tied to a specific concept.🔗https://t.co/LYnyNXnHye
📜 In-Context Learning Workshop organized by Paloma García de Herreros García, Israel A. Azime and Miaoran Zhang on June 12th from 2 pm to 5 pm.
More information 👇
https://t.co/h04FhRckmj
Drop by my talk at LREC-COLING on Thursday on unsupervised cognate induction between closely related data-imbalanced language pairs :) https://t.co/if2y7n1nRV
📢Our department LST in cooperation with DFKI is inviting applications for the W3 Professorship in Language Technology.
https://t.co/WWZrlFghUc
Please spread the word.
[1/4] Introducing “A Primer on the Inner Workings of Transformer-based Language Models”, a comprehensive survey on interpretability methods and the findings into the functioning of language models they have led to.
ArXiv: https://t.co/UBh2ZLmYkr
Incredibly proud of our teamwork, now in @icmlconf! This position starts a series of work on data-driven scientific discovery w generative models.
Follow-ups coming soon on benchmarks, systems, & accessibility in science!
https://t.co/FzqbJQm8F4
#ICML2024@allen_ai@ai2_aristo
🌻 Super excited about my first Computer Science publication at @naaclmeeting (main)! @mbodhisattwa and I study the language of deception and how language models fare at detecting them. And guess what we've found: https://t.co/wQLHS5F1XZ
(1/n) 🧵
@EconUofU @allen_ai