Papers by Zongjie Li
Split and Merge: Aligning Position Biases in LLM-based Evaluators (2024.emnlp-main)
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| Challenge: | Large language models (LLMs) have shown promise as automated evaluators for assessing the quality of answers generated by AI systems. |
| Approach: | They propose an alignment-based system that calibrates position bias in a lightweight yet effective manner by taking into account both length and semantics and combining them into a single prompt. |
| Outcome: | Extensive experiments with six LLMs on 11,520 answer pairs show that PORTIA significantly improves consistency and consistency rates with humans. |