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Found 4 papers, 4 papers with code
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
Memorization in language models is typically treated as a homogenous phenomenon, neglecting the specifics of the memorized data.
Emergent and Predictable Memorization in Large Language Models
Memorization, or the tendency of large language models (LLMs) to output entire sequences from their training data verbatim, is a key concern for safely deploying language models.
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)
GPT-NeoX-20B: An Open-Source Autoregressive Language Model
We introduce GPT-NeoX-20B, a 20 billion parameter autoregressive language model trained on the Pile, whose weights will be made freely and openly available to the public through a permissive license.
Ranked #40 on
Multi-task Language Understanding
on MML
