Papers by Adithya Samavedhi
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank (2023.findings-emnlp)
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| Challenge: | Existing methods for supervised OOD detection require expensive manual annotation of in-distribution and OOD samples. |
| Approach: | They propose a self-supervised OOD detection method that requires only in-distribution samples as supervision. |
| Outcome: | Experiments with multiple classifiers on coarse- and fine-grained datasets show the proposed method performs well in both coarse-and fine-grid settings. |
Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis (2023.findings-eacl)
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| Challenge: | Recent advances in the area of long document matching have primarily focused on using transformer-based models for long document encoding and matching. |
| Approach: | They propose to use simple neural models and simple embeddings to improve document matching by taking significantly less training time, energy, and memory. |
| Outcome: | The proposed models outperform the more complex BERT-based models while taking significantly less training time, energy, and memory. |