Papers by Mehwish Alam
On the Impact of Temporal Representations on Metaphor Detection (2022.lrec-1)
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| Challenge: | State-of-the-art approaches for metaphor detection compare their literal - or core - meaning and their contextual meaning using neural networks. |
| Approach: | They propose to use temporal and static word embeddings to account for different representations of literal meanings to examine metaphor detection tasks. |
| Outcome: | The proposed method outperforms static methods but may provide representations of the core meaning of the metaphor too close to their contextual meaning, causing confusion. |
It’s All About the Confidence: An Unsupervised Approach for Multilingual Historical Entity Linking using Large Language Models (2026.eacl-long)
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| Challenge: | Existing approaches to EL for historical texts require substantial training data or rely on domain-specific rules that limit scalability. |
| Approach: | They propose an unsupervised ensemble approach combining a Small Language Model and an LLM for historical EL. |
| Outcome: | The proposed approach outperforms state-of-the-art models on four established benchmarks in six European languages from the 19th and 20th centuries. |