From the 1 of 5 linked papers with an AI index.
5 papers
Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction
Hanhua Hong, Yizhi Li, Jiaoyan Chen +4
The paper conducts a meta‑evaluation of rubrics generated by large language models for assessing the reproducibility of research papers, comparing intrinsic semantic similarity and…
The Achilles' Heel of Angular Margins: A Chebyshev Polynomial Fix for Speaker Verification
Yang Wang, Yiqi Liu, Chenghao Xiao +1
Angular margin losses, such as AAM-Softmax, have become the de facto in speaker and face verification. Their success hinges on directly manipulating the angle between features and…
RIGOURATE: Quantifying Scientific Exaggeration with Evidence-Aligned Claim Evaluation
Joseph James, Chenghao Xiao, Yucheng Li +2
Scientific rigour tends to be sidelined in favour of bold statements, leading authors to overstate claims beyond what their results support. We present RIGOURATE, a two-stage multi…
ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation
Xiao Wang, Daniil Larionov, Siwei Wu +4
Evaluating the quality of generated text automatically remains a significant challenge. Conventional reference-based metrics have been shown to exhibit relatively weak correlation…
Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Prompts
Hanhua Hong, Chenghao Xiao, Yang Wang +3
Evaluating natural language generation systems is challenging due to the diversity of valid outputs. While human evaluation is the gold standard, it suffers from inconsistencies, l…