4 citations · 17 across the 11 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…
Findings of the BlackboxNLP 2025 Shared Task: Localizing Circuits and Causal Variables in Language Models
Dana Arad, Yonatan Belinkov, Hanjie Chen +5
Mechanistic interpretability (MI) seeks to uncover how language models (LMs) implement specific behaviors, yet measuring progress in MI remains challenging. The recently released M…
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…
CRISP: Persistent Concept Unlearning via Sparse Autoencoders
Tomer Ashuach, Dana Arad, Aaron Mueller +2
As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preserving model utility has become pa…
Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics
Yaniv Nikankin, Anja Reusch, Aaron Mueller +1
Do large language models (LLMs) solve reasoning tasks by learning robust generalizable algorithms, or do they memorize training data? To investigate this question, we use arithmeti…