most citedSpherical Position Encoding for Transformers

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023

Translation Aligned Sentence Embeddings for Turkish Language

Eren Unlu, Unver Ciftci

Due to the limited availability of high quality datasets for training sentence embeddings in Turkish, we propose a training methodology and a regimen to develop a sentence embeddin…

cs.LG2023

Entity Embeddings : Perspectives Towards an Omni-Modality Era for Large Language Models

Eren Unlu, Unver Ciftci

Large Language Models (LLMs) are evolving to integrate multiple modalities, such as text, image, and audio into a unified linguistic space. We envision a future direction based on…

cs.CL20231 cited

Spherical Position Encoding for Transformers

Eren Unlu

Position encoding is the primary mechanism which induces notion of sequential order for input tokens in transformer architectures. Even though this formulation in the original tran…

cs.CL2023

Chatmap : Large Language Model Interaction with Cartographic Data

Eren Unlu

The swift advancement and widespread availability of foundational Large Language Models (LLMs), complemented by robust fine-tuning methodologies, have catalyzed their adaptation fo…

cs.CL2023

FootGPT : A Large Language Model Development Experiment on a Minimal Setting

Eren Unlu

With recent empirical observations, it has been argued that the most significant aspect of developing accurate language models may be the proper dataset content and training strate…

cs.AI20231 cited

Structural Embeddings of Tools for Large Language Models

Eren Unlu

It is evident that the current state of Large Language Models (LLMs) necessitates the incorporation of external tools. The lack of straightforward algebraic and logical reasoning i…