MUMBAI, India, June 20 -- Intellectual Property India has published a patent application (202321086642 A) filed by Tata Consultancy Services Limited, Maharashtra, on Dec. 18, 2023, for 'perplexity and log-likelihood based approach for text classification using causal language models.'
Inventor(s) include Pawar, Sachin Sharad; Ramrakhiyani, Nitin Vijaykumar; Sinha, Anubhav; Apte, Manoj Madhav; and Palshikar, Girish Keshav.
The application for the patent was published on June 20, under issue no. 25/2025.
According to the abstract released by the Intellectual Property India: "State of art techniques using moderate sized Language Models (LMs) for text classification need fine-tuning or in-context learning. A method and system providing a two-step classification using moderate-sized (#params = 2.7B) causal LM (Gen AI) is disclosed. Firstly, for a text instance to be classified, a set of perplexity and log-likelihood based features are obtained from an LM. Further, a light-weight classifier is trained in the second step to predict the final label. The system enables a new way of exploiting the available labelled instances, in addition to the existing ways like fine-tuning LMs or in-context learning. It neither needs any parameter updates in LMs like fine-tuning nor it is restricted by the number of training examples to be provided in the prompt like in-context learning. The key advantages of the disclosed system are explainability through most suitable key phrases and its applicability in resource poor environment."
Disclaimer: Curated by HT Syndication.
