Imagen de Portada

The advantages of context specific language models: the case of the Erasmian Language Model

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gonçalves, João, Jelicic, Nick, Murgia, Michele, Stamhuis, Evert
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training
por: Kloots, Marianne de Heer, et al.
Publicado: (2025)

Can large language models explore in-context?
por: Krishnamurthy, Akshay, et al.
Publicado: (2024)

A survey of textual cyber abuse detection using cutting-edge language models and large language models
por: Diaz-Garcia, Jose A., et al.
Publicado: (2025)

One Thousand and One Pairs: A "novel" challenge for long-context language models
por: Karpinska, Marzena, et al.
Publicado: (2024)

Are language models rational? The case of coherence norms and belief revision
por: Hofweber, Thomas, et al.
Publicado: (2024)

A thorough benchmark of automatic text classification: From traditional approaches to large language models
por: Cunha, Washington, et al.
Publicado: (2025)

Emission-GPT: A domain-specific language model agent for knowledge retrieval, emission inventory and data analysis
por: Ye, Jiashu, et al.
Publicado: (2025)

On the generalization of language models from in-context learning and finetuning: a controlled study
por: Lampinen, Andrew K., et al.
Publicado: (2025)

Large language models for folktale type automation based on motifs: Cinderella case study
por: Arčon, Tjaša, et al.
Publicado: (2025)

Dissociating language and thought in large language models
por: Mahowald, Kyle, et al.
Publicado: (2023)

Where does In-context Translation Happen in Large Language Models
por: Sia, Suzanna, et al.
Publicado: (2024)

ChatGPT Alternative Solutions: Large Language Models Survey
por: Alipour, Hanieh, et al.
Publicado: (2024)

Large Language Models Can Self-Improve in Long-context Reasoning
por: Li, Siheng, et al.
Publicado: (2024)

Concept-aware Data Construction Improves In-context Learning of Language Models
por: Štefánik, Michal, et al.
Publicado: (2024)

Supervised Knowledge Makes Large Language Models Better In-context Learners
por: Yang, Linyi, et al.
Publicado: (2023)

In-context Language Learning for Endangered Languages in Speech Recognition
por: Li, Zhaolin, et al.
Publicado: (2025)

Fluent dreaming for language models
por: Thompson, T. Ben, et al.
Publicado: (2024)

Algorithmic progress in language models
por: Ho, Anson, et al.
Publicado: (2024)

Large language models can accurately predict searcher preferences
por: Thomas, Paul, et al.
Publicado: (2023)

On the attribution of confidence to large language models
por: Keeling, Geoff, et al.
Publicado: (2024)

Large language models and linguistic intentionality
por: Grindrod, Jumbly
Publicado: (2024)

Do language models practice what they preach? Examining language ideologies about gendered language reform encoded in LLMs
por: Watson, Julia, et al.
Publicado: (2024)

Enriching language models with graph-based context information to better understand textual data
por: Roethel, Albert, et al.
Publicado: (2023)

Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted Narratives
por: Zhang, Xinliang Frederick, et al.
Publicado: (2024)

PRIME: Large Language Model Personalization with Cognitive Dual-Memory and Personalized Thought Process
por: Zhang, Xinliang Frederick, et al.
Publicado: (2025)

Evaluating the Meta- and Object-Level Reasoning of Large Language Models for Question Answering
por: Ferguson, Nick, et al.
Publicado: (2025)

SHARE: Social-Humanities AI for Research and Education
por: Gonçalves, João, et al.
Publicado: (2026)

Are Large Language Models Good In-context Learners for Financial Sentiment Analysis?
por: Wei, Xinyu, et al.
Publicado: (2025)

Multimodal In-context Learning for ASR of Low-resource Languages
por: Li, Zhaolin, et al.
Publicado: (2026)

Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language Model
por: Gao, Chaochen, et al.
Publicado: (2024)

Linguistic traces of stochastic empathy in language models
por: Kleinberg, Bennett, et al.
Publicado: (2024)

Infusing clinical knowledge into tokenisers for language models
por: Hasan, Abul, et al.
Publicado: (2024)

CONFLARE: CONFormal LArge language model REtrieval
por: Rouzrokh, Pouria, et al.
Publicado: (2024)

Output Scouting: Auditing Large Language Models for Catastrophic Responses
por: Bell, Andrew, et al.
Publicado: (2024)

InstructionCP: A fast approach to transfer Large Language Models into target language
por: Chen, Kuang-Ming, et al.
Publicado: (2024)

Multilingual Large Language Models do not comprehend all natural languages to equal degrees
por: Moskvina, Natalia, et al.
Publicado: (2026)

Linguistic Fingerprint in Transformer Models: How Language Variation Influences Parameter Selection in Irony Detection
por: Mastromattei, Michele, et al.
Publicado: (2024)

In-context Pretraining: Language Modeling Beyond Document Boundaries
por: Shi, Weijia, et al.
Publicado: (2023)

What do language models model? Transformers, automata, and the format of thought
por: Klein, Colin
Publicado: (2025)

A Role-specific Guided Large Language Model for Ophthalmic Consultation Based on Stylistic Differentiation
por: Fu, Laiyi, et al.
Publicado: (2024)