Papers by Zhexiao Lin
BBScoreV2: Learning Time-Evolution and Latent Alignment from Stochastic Representation (2025.emnlp-main)
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| Challenge: | Autoregressive generative models are gaining traction in language tasks such as text generation and machine translation. |
| Approach: | They propose a likelihood-based evaluation metric that fits transformer-based model embeddings into a stochastic process and propose it as a probability-based metric. |
| Outcome: | The proposed model embeddings induce a "clustered-to-temporal ordered" mapping of language model representations in high-dimensional space, and this structure enhances performance on tasks such as temporal consistency evaluation and AI-generated content detection. |