Language Models as a Service: Overview of a New Paradigm and its Challenges

September 28, 2023 Β· Declared Dead Β· πŸ› Journal of Artificial Intelligence Research

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Authors Emanuele La Malfa, Aleksandar Petrov, Simon Frieder, Christoph Weinhuber, Ryan Burnell, Raza Nazar, Anthony G. Cohn, Nigel Shadbolt, Michael Wooldridge arXiv ID 2309.16573 Category cs.AI: Artificial Intelligence Cross-listed cs.CL, cs.CY Citations 13 Venue Journal of Artificial Intelligence Research Last Checked 4 months ago
Abstract
Some of the most powerful language models currently are proprietary systems, accessible only via (typically restrictive) web or software programming interfaces. This is the Language-Models-as-a-Service (LMaaS) paradigm. In contrast with scenarios where full model access is available, as in the case of open-source models, such closed-off language models present specific challenges for evaluating, benchmarking, and testing them. This paper has two goals: on the one hand, we delineate how the aforementioned challenges act as impediments to the accessibility, replicability, reliability, and trustworthiness of LMaaS. We systematically examine the issues that arise from a lack of information about language models for each of these four aspects. We conduct a detailed analysis of existing solutions and put forth a number of considered recommendations, and highlight the directions for future advancements. On the other hand, it serves as a comprehensive resource for existing knowledge on current, major LMaaS, offering a synthesized overview of the licences and capabilities their interfaces offer.
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