8 citations · 17 across the 15 of their papers we have counts for
5 papers · 1 filter
The Interlingua Hypothesis: LLMs Translate via a Latent Task-agnostic Feature Space
Jacob Brinton, Jannik Brinkmann, Mark Crovella +1
Large language models (LLMs) have recently demonstrated improved machine translation performance over strong supervised baselines. This raises questions as to what mechanisms under…
Mood Matters: How Syntactic Sensitivity Undermines Safety Alignment
Alina Klerings, Jannik Brinkmann, Heiner Stuckenschmidt +1
Large language models typically undergo post-training to align them with safety policies but there exist many sophisticated jailbreaks that sidestep established safeguards. For ins…
In-Context Algebra
Eric Todd, Jannik Brinkmann, Rohit Gandikota +1
We investigate the mechanisms that arise when transformers are trained to solve arithmetic on sequences where tokens are variables whose meaning is determined only through their in…
In-Context Learning Beyond Copying: A Training-Time Analysis of Abstractive ICL
Kerem Sahin, Sheridan Feucht, Adam Belfki +4
The sudden emergence of induction circuits and the ability to perform in-context copying in LLMs coincides with a sharp drop in training loss over a short span of the training proc…
Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages
Jannik Brinkmann, Chris Wendler, Christian Bartelt +1
Human bilinguals often use similar brain regions to process multiple languages, depending on when they learned their second language and their proficiency. In large language models…