Papers by Maksym Del
Cross-lingual Similarity of Multilingual Representations Revisited (2022.aacl-main)
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| Challenge: | Similarity indexes like CKA and CCA are not suitable for cross-lingual learning analysis. |
| Approach: | They propose an alternative that is exempt from the difficulties of CKA/CCA and is good specifically in a cross-lingual context. |
| Outcome: | The proposed method is exempt from the difficulties of CKA/CCA and is good specifically in a cross-lingual context. |
To Err Is Human, but Llamas Can Learn It Too (2024.findings-emnlp)
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| Challenge: | Specifically, we fine-tune Llama 2 LMs for error generation and find that this approach yields synthetic errors akin to human errors. |
| Approach: | They propose to fine-tune Llama 2 LMs for error generation and train GEC Llma models using these artificial errors. |
| Outcome: | The proposed approach outperforms state-of-the-art models with gains ranging between 0.8 and 6 F0.5 points across all languages tested. |
True Detective: A Deep Abductive Reasoning Benchmark Undoable for GPT-3 and Challenging for GPT-4 (2023.starsem-1)
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| Challenge: | Large language models (LLMs) have demonstrated solid zero-shot reasoning capabilities, which is reflected in their performance on the current test tasks. |
| Approach: | They propose a benchmark consisting of 191 long-form mystery narratives constructed as detective puzzles. |
| Outcome: | The proposed benchmark outperforms random models on the current test tasks while state-of-the-art models only solve 38% of puzzles. |