Train and Fine-Tune Sentence Transformers Models

Training and Finetuning Embedding Models with Sentence Transformers

Training and Finetuning Sparse Embedding Models with Sentence Transformers

Train 400x faster Static Embedding Models with Sentence Transformers

Training and Finetuning Reranker Models with Sentence Transformers

Introduction to Transformers: an NLP Perspective

arXiv:2311. 17633v2 Announce Type: replace-cross Abstract: Transformers have dominated empirical machine learning models of natural language processing.

Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers

Train a Sentence Embedding Model with 1B Training Pairs

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

TimpaTeks: Automatic In-place Text Sequence Modification via Diffusion Language Model Steering

arXiv:2606. 08408v1 Announce Type: cross Abstract: We extend activation steering to diffusion language models (DLMs) and study a novel problem that arose due to the inference mechanism of DLMs: Modifying a text in-place to manifest a different concept.

An expressivity analysis of hierarchical modelling in deep transformers via bounded-depth grammars

Deep neural networks are widely believed to derive their expressive power from their ability to form \textbf{hierarchical representations}, capturing progressively more abstract and compositional features across layers. In language modeling, \textbf{transformers} have emerged as the dominant architecture, with early layers capturing local syntactic patterns and later layers encoding more complex clause-level dependencies.

An expressivity analysis of hierarchical modelling in deep transformers via bounded-depth grammars

arXiv:2606. 17522v1 Announce Type: cross Abstract: Deep neural networks are widely believed to derive their expressive power from their ability to form \textbf{hierarchical representations}, capturing progressively more abstract and compositional features across layers.

Multimodal Embedding & Reranker Models with Sentence Transformers