Papers by Shoaib Alam
LEGOBench: Scientific Leaderboard Generation Benchmark (2024.findings-emnlp)
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| Challenge: | a growing number of papers make it difficult to stay informed about the latest state-of-the-art research. |
| Approach: | They propose a benchmark to evaluate systems that generate scientific leaderboards . they use 22 years of submission data on arXiv and 11k machine learning leaderboard data on paperswithcode . |
| Outcome: | The proposed model shows significant performance gaps in the LEGOBench model . the model is based on a language model and four graph-based leaderboard generation task configuration . |