Salvato in:
| Autori principali: | , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2509.22030 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866914058050994176 |
|---|---|
| author | Zve, Evangelia Icard, Benjamin Breton, Alice Sainero, Lila Bourgne, Gauvain Ganascia, Jean-Gabriel |
| author_facet | Zve, Evangelia Icard, Benjamin Breton, Alice Sainero, Lila Bourgne, Gauvain Ganascia, Jean-Gabriel |
| contents | This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. Using vector embeddings from state-of-the-art language models and a cumulative clustering approach, we track their evolution over time in French and English news datasets focused on corporate social responsibility and climate change. The results reveal a consistent pattern: outliers tend to evolve into coherent topics over time across both models and languages. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22030 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Outliers to Topics in Language Models: Anticipating Trends in News Corpora Zve, Evangelia Icard, Benjamin Breton, Alice Sainero, Lila Bourgne, Gauvain Ganascia, Jean-Gabriel Computation and Language This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. Using vector embeddings from state-of-the-art language models and a cumulative clustering approach, we track their evolution over time in French and English news datasets focused on corporate social responsibility and climate change. The results reveal a consistent pattern: outliers tend to evolve into coherent topics over time across both models and languages. |
| title | From Outliers to Topics in Language Models: Anticipating Trends in News Corpora |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2509.22030 |