Papers with full complexity
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference (N18-1)
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| Challenge: | et al., 1996, show that many of the most actively studied problems in NLP depend in large part on natural language understanding (NLU). |
| Approach: | They propose a dataset for machine learning that uses ten different genres of English to evaluate sentences for their meanings. |
| Outcome: | The multi-genre natural language inference corpus is one of the largest available for natural language understanding. |
GAMIC: Graph-Aligned Molecular In-context Learning for Molecule Analysis via LLMs (2025.findings-emnlp)
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| Challenge: | Current methods for retrieving large language models rely on molecule feature similarity, such as Morgan fingerprints, which do not adequately capture the global molecular and atom-binding relationships. |
| Approach: | They propose a self-supervised learning technique that embeds demonstration examples into the input prompt. |
| Outcome: | The proposed technique outperforms simple Morgan-based retrieval methods across tasks by up to 45%. |