Sabiá: Portuguese large language models
As the capabilities of language models continue to advance, it is conceivable that “one-size-
fits-all” model will remain as the main paradigm. For instance, given the vast number of …
fits-all” model will remain as the main paradigm. For instance, given the vast number of …
Prometheus 2: An open source language model specialized in evaluating other language models
Proprietary LMs such as GPT-4 are often employed to assess the quality of responses from
various LMs. However, concerns including transparency, controllability, and affordability …
various LMs. However, concerns including transparency, controllability, and affordability …
Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration
Despite efforts to expand the knowledge of large language models (LLMs), knowledge gaps-
-missing or outdated information in LLMs--might always persist given the evolving nature of …
-missing or outdated information in LLMs--might always persist given the evolving nature of …
MoDE: CLIP Data Experts via Clustering
The success of contrastive language-image pretraining (CLIP) relies on the supervision from
the pairing between images and captions which tends to be noisy in web-crawled data. We …
the pairing between images and captions which tends to be noisy in web-crawled data. We …
Qurating: Selecting high-quality data for training language models
Selecting high-quality pre-training data is important for creating capable language models,
but existing methods rely on simple heuristics. We introduce QuRating, a method for …
but existing methods rely on simple heuristics. We introduce QuRating, a method for …
AboutMe: Using self-descriptions in webpages to document the effects of english pretraining data filters
Large language models'(LLMs) abilities are drawn from their pretraining data, and model
development begins with data curation. However, decisions around what data is retained or …
development begins with data curation. However, decisions around what data is retained or …
Tiny Models are the Computational Saver for Large Models
This paper introduces TinySaver, an early-exit-like dynamic model compression approach
which employs tiny models to substitute large models adaptively. Distinct from traditional …
which employs tiny models to substitute large models adaptively. Distinct from traditional …
An introduction to vision-language modeling
Following the recent popularity of Large Language Models (LLMs), several attempts have
been made to extend them to the visual domain. From having a visual assistant that could …
been made to extend them to the visual domain. From having a visual assistant that could …
Pedagogical Alignment of Large Language Models (LLM) for Personalized Learning: A Survey, Trends and Challenges
MA Razafinirina, WG Dimbisoa, T Mahatody - Journal of Intelligent …, 2024 - scirp.org
This survey paper investigates how personalized learning offered by Large Language
Models (LLMs) could transform educational experiences. We explore Knowledge Editing …
Models (LLMs) could transform educational experiences. We explore Knowledge Editing …
Lemoe: Advanced mixture of experts adaptor for lifelong model editing of large language models
Large language models (LLMs) require continual knowledge updates to stay abreast of the
ever-changing world facts, prompting the formulation of lifelong model editing task. While …
ever-changing world facts, prompting the formulation of lifelong model editing task. While …