Papers by Helia Hashemi
LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts (2024.acl-long)
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| Challenge: | Existing frameworks for the automated evaluation of natural language texts are based on a large language model (LLM) that fails to agree with human judges and is not fully validated by the human judges. |
| Approach: | They propose a large language model (LLM) that generates a distribution over potential responses to assess multiple dimensions of interest. |
| Outcome: | The proposed framework predicts human judges' assessment of user satisfaction on a scale of 1–4 with an RMS error 0.5, a 2 improvement over the uncalibrated baseline. |