Papers by Karen Hambardzumyan
LM Transparency Tool: Interactive Tool for Analyzing Transformer Language Models (2024.acl-demos)
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| Challenge: | Existing tools focus on isolated parts of the decision-making process, but LM-TT makes the entire prediction process transparent. |
| Approach: | They present an open-source toolkit for analyzing the internal workings of Transformer-based language models. |
| Outcome: | The LM Transparency Tool makes the entire prediction process transparent . it shows the importance of specific component at each step . |
WARP: Word-level Adversarial ReProgramming (2021.acl-long)
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| Challenge: | Existing approaches to transfer learning from pretrained language models are frozen and a task-specific head is trained on top of them. |
| Approach: | They propose an alternative approach that trains one or more task-specific layers on top of the language model. |
| Outcome: | The proposed approach outperforms existing methods on the GLUE leaderboard with just 32 training samples. |