In this paper, we present TimeLMs, a set of language models specialized on diachronic Twitter data. We show that a continual learning strategy contributes to ...

Feb 8, 2022 · In this paper, we present TimeLMs, a set of language models specialized on diachronic Twitter data. We show that a continual learning strategy contributes to ...

TimeLMs allows for easy access to models continuously trained on social media over regular intervals for researching language model degradation, ...

A large collection of time series data derived from Twitter, postprocessed using word embedding techniques, as well as specialized fine-tuned language models, ...

May 22, 2022 · In this paper, we present. TimeLMs, a set of language models specialized on diachronic Twitter data. We show that a con- tinual learning ...

... language model literature. In this paper, we present TimeLMs, a set of language models specialized on diachronic Twitter data. We show that a continual ...

Feb 8, 2022 · We show that a continual learning strategy contributes to enhancing Twitter-based language models' capacity to deal with future and out-of- ...

Sep 10, 2024 · We show that a continual learning strategy contributes to enhancing Twitter-based language models' capacity to deal with future and out-of- ...

To accommodate emerging and future language models, we develop a flexible framework that incorporates any text encoder as a plug-in to obtain the textual ...

Apr 1, 2022 · In this paper, we present TimeLMs, a set of language models specialized on diachronic Twitter data. We show that a continual learning strategy ...