arXiv Machine Learning By Baishi Li, Ta Yu, Kelvin J. L. Koa, Ke-Wei Huang

The Proxy Presumption: From Semantic Embeddings to Valid Social Measures

Read the original on arXiv Machine Learning →

arXiv:2605. 07409v2 Announce Type: replace-cross Abstract: Natural Language Processing is rapidly evolving into a primary instrument for Computational Social Science, with researchers increasingly using embeddings to measure latent constructs such as novelty, creativity, and bias.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv AI
Aug 11

Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation

arXiv:2510. 21891v2 Announce Type: replace-cross Abstract: To deploy large language models (LLMs) in high-stakes application domains that require substantively accurate responses to open-ended prompts, we need reliable, computationally inexpensive methods that assess the trustworthiness of long-form responses generated by LLMs.

By Dhrupad Bhardwaj, Julia Kempe, Tim G. J. Rudner