PL
Percy Liang
Associate Professor & Director, Center for Research on Foundation Models
Stanford University
Coining 'foundation models' and leading transparency benchmarks like HELM and the Foundation Model Transparency Index.
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Economic Evaluations of Language Models
arXiv:2607.19375v1 Announce Type: new Abstract: Language models perform economically valuable work, yet they are not currently assessed for how well they perform every economically valuable task. We introduce EconEvals as an open-source evaluation suite to measure capabilities relevant to tasks, work activities, and occupations in the US labor economy. We ground the evaluation suite in real user queries to language models where possible, and supplement these with synthetic data. Our evaluations
LinkBERT: Pretraining Language Models with Document Links
Language model (LM) pretraining captures various knowledge from text corpora, helping downstream NLP tasks. However, existing methods such as BERT model a single document, failing to capture document dependencies and knowledge that spans across documents. In this work, we propose LinkBERT, an effective LM pretraining method that incorporates document links, such as hyperlinks. Given a pretraining corpus, we view it as a graph of documents, and create LM inputs by placing linked documents in the