---
title: "Who cites Temporal Effects on Pre-trained — 44 citing papers"
description: "44 papers of the Elamur Research library cite «Temporal Effects on Pre-trained Models for Language Processing Tasks», found in their…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Temporal Effects on Pre-trained Models for…](https://md.research.elamur.ai/free/en/papers/agarwal-2022-temporal-effects-pre-trained-models/) / cited by

# Who cites «Temporal Effects on Pre-trained Models for Language Processing Tasks»

44 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Temporal Effects on Pre-trained Models for Language Processing Tasks»](https://md.research.elamur.ai/free/en/papers/agarwal-2022-temporal-effects-pre-trained-models/)

1. **[TimeLMs: Diachronic Language Models from Twitter](https://md.research.elamur.ai/free/en/papers/loureiro-2022-timelms-diachronic-language-models-twitter/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Loureiro, Francesco Barbieri, Leonardo Neves, et al.*2022 · 331 citations*
2. **[DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 259 citations*
3. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
4. [**Are Large Language Models Robust Coreference Resolvers? arXiv:2305.14489**Nghia T. Le, Alan Ritter*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/le-2023-large-language-models-robust-coreference/)
5. **[From Adoption to Adaptation: Tracing the Diffusion of New Emojis on Twitter](https://md.research.elamur.ai/free/en/papers/zhou-2026-adoption-adaptation-tracing-diffusion-new/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Yuhang Zhou, Xuan Lu, Wei Ai*2026*
6. **[Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation](https://md.research.elamur.ai/free/en/papers/liu-2026-knowledge-driven-augmentation-retrieval-integrative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weisi Liu, Guangzeng Han, Xiaolei Huang*2026*
7. **[Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance](https://md.research.elamur.ai/free/en/papers/seegmiller-2026-measuring-distribution-shift-user-prompts/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Seegmiller, Sarah Masud Preum*2026*

37 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/agarwal-2022-temporal-effects-pre-trained-models/) — Temporal Effects on Pre-trained Models for Language Processing Tasks