Papers with model-generated rationales
RORA: Robust Free-Text Rationale Evaluation (2024.acl-long)
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| Challenge: | Existing metrics rely on degree to which rationale supports a label, but they fail to evaluate rationales that inadvertently leak the label. |
| Approach: | They propose a RObust free-text RAtionale evaluation against label leakage that quantifies the new information supplied by a rationale to justify the label. |
| Outcome: | The proposed evaluation outperforms existing methods in evaluating human-written, synthetic, or model-generated rationales, particularly demonstrating robustness against label leakage. |
Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study (2025.coling-main)
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| Challenge: | Existing evaluation approaches to evaluate Large Language Models are affected by potential biases within LLMs. |
| Approach: | They propose two many-shot In-Context Learning (ICL) prompt templates to help LLM evaluators mitigate potential biases. |
| Outcome: | The proposed templates reduce biases by using in-context examples with model-generated rationales as references. |