3 papers
cs.CL2025
Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipeline
Meng Lu, Ruochen Zhang, Carsten Eickhoff +1
Multilingual large language models (LLMs) often exhibit factual inconsistencies across languages, with significantly better performance in factual recall tasks in English than in o…
cs.CL2025
Talking Heads: Understanding Inter-layer Communication in Transformer Language Models
Jack Merullo, Carsten Eickhoff, Ellie Pavlick
Although it is known that transformer language models (LMs) pass features from early layers to later layers, it is not well understood how this information is represented and route…
cs.IR2025
Axiomatic Causal Interventions for Reverse Engineering Relevance Computation in Neural Retrieval Models
Catherine Chen, Jack Merullo, Carsten Eickhoff
Neural models have demonstrated remarkable performance across diverse ranking tasks. However, the processes and internal mechanisms along which they determine relevance are still l…