arXiv:2607. 19375v1 Announce Type: cross Abstract: Language models perform economically valuable work, yet they are not currently assessed for how well they perform every economically valuable task.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2606. 26118v1 Announce Type: cross Abstract: We work towards measuring both AI adoption and the capability of AI to perform discrete labor tasks across various occupations.
arXiv:2608. 05172v1 Announce Type: cross Abstract: The task-based framework in economics models occupations as bundles of tasks.
Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing benchmarks provide limited support for evaluating whether agents can carry out office-suite workflows at a reasonable cost.
arXiv:2607. 27155v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly expected to assist users in completing tasks.
arXiv:2607. 11889v1 Announce Type: cross Abstract: Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromises the validity of backtests and causal inference in finance and the social sciences.
OpenAI introduces GDPval, a new evaluation that measures model performance on real-world economically valuable tasks across 44 occupations.