most citedTimeLMs: Diachronic Language Models from Twitter

27 citations · 82 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL20225 cited

Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shifts

Asahi Ushio, Leonardo Neves, Vitor Silva +2

Recent progress in language model pre-training has led to important improvements in Named Entity Recognition (NER). Nonetheless, this progress has been mainly tested in well-format…

cs.CL202218 cited

Twitter Topic Classification

Dimosthenis Antypas, Asahi Ushio, Jose Camacho-Collados +3

Social media platforms host discussions about a wide variety of topics that arise everyday. Making sense of all the content and organising it into categories is an arduous task. A…

cs.CL202213 cited

TempoWiC: An Evaluation Benchmark for Detecting Meaning Shift in Social Media

Daniel Loureiro, Aminette D'Souza, Areej Nasser Muhajab +6

Language evolves over time, and word meaning changes accordingly. This is especially true in social media, since its dynamic nature leads to faster semantic shifts, making it chall…

cs.CL202227 cited

TimeLMs: Diachronic Language Models from Twitter

Daniel Loureiro, Francesco Barbieri, Leonardo Neves +2

Despite its importance, the time variable has been largely neglected in the NLP and language model literature. In this paper, we present TimeLMs, a set of language models specializ…

cs.CL20201 cited

The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks

Brihi Joshi, Neil Shah, Francesco Barbieri +1

Contextual embeddings derived from transformer-based neural language models have shown state-of-the-art performance for various tasks such as question answering, sentiment analysis…

cs.CL202018 cited

TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification

Francesco Barbieri, Jose Camacho-Collados, Leonardo Neves +1

The experimental landscape in natural language processing for social media is too fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics like sent…