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Found 8 papers, 2 papers with code
Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?
We then reveal the mechanism causing this degradation: downstream metrics require comparing the correct choice against a small number of specific incorrect choices, meaning accurately predicting downstream capabilities requires predicting not just how probability mass concentrates on the correct choice with scale, but also how probability mass fluctuates on specific incorrect choices with scale.
Visibility into AI Agents
Increased delegation of commercial, scientific, governmental, and personal activities to AI agents -- systems capable of pursuing complex goals with limited supervision -- may exacerbate existing societal risks and introduce new risks.
Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models
Public release of the weights of pretrained foundation models, otherwise known as downloadable access \citep{solaiman_gradient_2023}, enables fine-tuning without the prohibitive expense of pretraining.
Quality-Diversity through AI Feedback
In many text-generation problems, users may prefer not only a single response, but a diverse range of high-quality outputs from which to choose.
Challenges and Applications of Large Language Models
Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application areas.
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
How do large language models (LLMs) develop and evolve over the course of training?
Ranked #4 on
Language Modelling
on LAMBADA
(Perplexity metric)
Language Model Crossover: Variation through Few-Shot Prompting
The promise of such language model crossover (which is simple to implement and can leverage many different open-source language models) is that it enables a simple mechanism to evolve semantically-rich text representations (with few domain-specific tweaks), and naturally benefits from current progress in language models.
EleutherAI: Going Beyond "Open Science" to "Science in the Open"
Over the past two years, EleutherAI has established itself as a radically novel initiative aimed at both promoting open-source research and conducting research in a transparent, openly accessible and collaborative manner.
