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cs.CL2026
Fast & Faithful Function Vectors
Minh An Pham, Anton Segeler, Thomas Wiegand +4
Function vectors (FVs) are task representations elicited during in-context learning that can be used to steer Large Language Models (LLMs). However, design choices in their formula…
cs.CL2025
The Atlas of In-Context Learning: How Attention Heads Shape In-Context Retrieval Augmentation
Patrick Kahardipraja, Reduan Achtibat, Thomas Wiegand +2
Large language models are able to exploit in-context learning to access external knowledge beyond their training data through retrieval-augmentation. While promising, its inner wor…
cs.CL2024
AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers
Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer +4
Large Language Models are prone to biased predictions and hallucinations, underlining the paramount importance of understanding their model-internal reasoning process. However, ach…