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Found 8 papers, 2 papers with code
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models
On text benchmarks, Core not only performs competitively to other frontier models on a set of well-established benchmarks (e. g. MMLU, GSM8K) but also outperforms GPT4-0613 on human evaluation.
Synthesizer: Rethinking Self-Attention for Transformer Models
The dot product self-attention is known to be central and indispensable to state-of-the-art Transformer models.
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling
There are two major classes of natural language grammar -- the dependency grammar that models one-to-one correspondences between words and the constituency grammar that models the assembly of one or several corresponded words.
Surprise: Result List Truncation via Extreme Value Theory
Work in information retrieval has largely been centered around ranking and relevance: given a query, return some number of results ordered by relevance to the user.
Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study
Large generative language models such as GPT-2 are well-known for their ability to generate text as well as their utility in supervised downstream tasks via fine-tuning.
Synthesizer: Rethinking Self-Attention in Transformer Models
The dot product self-attention is known to be central and indispensable to state-of-the-art Transformer models.
Ranked #1 on
Dialogue Generation
on Persona-Chat
(BLEU-1 metric, using extra
training data)
Choppy: Cut Transformer For Ranked List Truncation
Work in information retrieval has traditionally focused on ranking and relevance: given a query, return some number of results ordered by relevance to the user.
Reverse Engineering Configurations of Neural Text Generation Models
This paper seeks to develop a deeper understanding of the fundamental properties of neural text generations models.
