Search Results for author:
Found 5 papers, 3 papers with code
Context versus Prior Knowledge in Language Models
To answer a question, language models often need to integrate prior knowledge learned during pretraining and new information presented in context.
Schrödinger's Bat: Diffusion Models Sometimes Generate Polysemous Words in Superposition
Recent work has shown that despite their impressive capabilities, text-to-image diffusion models such as DALL-E 2 (Ramesh et al., 2022) can display strange behaviours when a prompt contains a word with multiple possible meanings, often generating images containing both senses of the word (Rassin et al., 2022).
Equivariant Transduction through Invariant Alignment
The ability to generalize compositionally is key to understanding the potentially infinite number of sentences that can be constructed in a human language from only a finite number of words.
Examining the Inductive Bias of Neural Language Models with Artificial Languages
Since language models are used to model a wide variety of languages, it is natural to ask whether the neural architectures used for the task have inductive biases towards modeling particular types of languages.
A Non-Linear Structural Probe
Probes are models devised to investigate the encoding of knowledge -- e. g. syntactic structure -- in contextual representations.
