Papers by Philipp Wicke
Time Course MechInterp: Analyzing the Evolution of Components and Knowledge in Large Language Models (2025.findings-acl)
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| Challenge: | Large language models acquire and store factual knowledge for interpretability, reliability, efficiency . prior work on factual recall focused on localizing knowledge within transformer parameters . |
| Approach: | They analyze the evolution of factual knowledge representation in a large language model by tracking its attention heads and feed forward networks over training. |
| Outcome: | The proposed model acquires and stores factual knowledge over time and is adaptively trained . the proposed model can be pruned, optimized, and transparent . |
A Crosslingual Investigation of Conceptualization in 1335 Languages (2023.acl-long)
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Yihong Liu, Haotian Ye, Leonie Weissweiler, Philipp Wicke, Renhao Pei, Robert Zangenfeind, Hinrich Schütze
| Challenge: | Conceptualizer is a method that creates a bipartite directed alignment graph between source language concepts and sets of target language strings. |
| Approach: | They propose a method that creates a bipartite directed alignment graph between source language concepts and sets of target language strings. |
| Outcome: | The proposed method has good alignment accuracy across all languages and on 32 Swadesh concepts. |
Exploring Spatial Schema Intuitions in Large Language and Vision Models (2024.findings-acl)
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| Challenge: | Large language models excel in varied NLP tasks, but lack a direct connection between sensory perception and physical action. |
| Approach: | They examine whether large language models capture implicit human intuitions about building blocks of language . they employ spatial cognitive foundations developed through early sensorimotor experiences . |
| Outcome: | The proposed model captures implicit human intuitions about building blocks of language without a tangible connection to embodied experiences. |
LMs stand their Ground: Investigating the Effect of Embodiment in Figurative Language Interpretation by Language Models (2023.findings-acl)
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| Challenge: | Figures are based on the use of words in a way that deviates from their conventional order and meaning. |
| Approach: | They propose to use a figurative language model to interpret embodied metaphors by using larger language models that conceptualise embodies the action of the metaphorical sentence. |
| Outcome: | The proposed model enables interpretation of figurative language when the action of the metaphorical sentence is more embodied. |