3 papers
cs.CL2026
Causal Drawbridges: Characterizing Gradient Blocking of Syntactic Islands in Transformer LMs
Sasha Boguraev, Kyle Mahowald
We show how causal interventions in Transformer models provide insights into English syntax by focusing on a long-standing challenge for syntactic theory: syntactic islands. Extrac…
cs.CL2025
Causal Interventions Reveal Shared Structure Across English Filler-Gap Constructions
Sasha Boguraev, Christopher Potts, Kyle Mahowald
Language Models (LMs) have emerged as powerful sources of evidence for linguists seeking to develop theories of syntax. In this paper, we argue that causal interpretability methods…
cs.AI2024
Models Can and Should Embrace the Communicative Nature of Human-Generated Math
Sasha Boguraev, Ben Lipkin, Leonie Weissweiler +1
Math is constructed by people for people: just as natural language corpora reflect not just propositions but the communicative goals of language users, the math data that models ar…