Papers by Sindhu Kishore
Unveiling Divergent Inductive Biases of LLMs on Temporal Data (2024.naacl-short)
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| Challenge: | Temporal relations play a crucial role across diverse applications, including event summarization, predicting future events and medical information processing. |
| Approach: | They evaluate the performance of large language models in the analysis of temporal data using two prompt types, Question Answering and Textual Entailment. |
| Outcome: | The proposed models show that they are biased towards specific temporal relationships, while GPT-3.5 prefers “AFTER” for implicit and explicit events, while TE models lean towards “BEFORE”. |