Papers by Saurabh Kulshreshtha
Cross-lingual Alignment Methods for Multilingual BERT: A Comparative Study (2020.findings-emnlp)
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| Challenge: | Multilingual BERT (mBERT) has shown reasonable capability for zero-shot cross-lingual transfer when fine-tuned on downstream tasks. |
| Approach: | They propose to use parallel corpora and rotational alignment methods to improve transfer performance in a zero-shot setting. |
| Outcome: | The proposed method improves rotation-based alignment on Name Entity Recognition and Semantic Slot Filling tasks. |
Down and Across: Introducing Crossword-Solving as a New NLP Benchmark (2022.acl-long)
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| Challenge: | Recent advances in NLP have led to a growing demand for challenging tasks. |
| Approach: | They propose to solve crossword puzzles as a natural language understanding task . they release a corpus of crossword clues from the daily crossword spanning 25 years . |
| Outcome: | The proposed task is based on a corpus of crossword puzzles from the new york times daily crossword spanning 25 years . the dataset contains over half a million unique clue-answer pairs . |
BERT Busters: Outlier Dimensions that Disrupt Transformers (2021.findings-acl)
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| Challenge: | Existing studies show that pre-trained Transformers are remarkably robust to pruning. |
| Approach: | They show that pre-trained Transformer encoders are surprisingly fragile to pruning . they show that disabling them significantly degrades both the MLM loss and the downstream task performance. |
| Outcome: | The results show that the removal of features in pre-trained transformers significantly degrades both the MLM loss and the downstream task performance. |