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Found 6 papers, 3 papers with code
IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations
Current foundation models exhibit impressive capabilities when prompted either with text only or with both image and text inputs.
DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models
Large language models (LLMs) are increasingly used across society, including in domains like business, engineering, and medicine.
On Retrieval Augmentation and the Limitations of Language Model Training
Augmenting a language model (LM) with $k$-nearest neighbors ($k$NN) retrieval on its training data alone can decrease its perplexity, though the underlying reasons for this remain elusive.
Interpretable Diffusion via Information Decomposition
For diffusion models, we show that a natural non-negative decomposition of mutual information emerges, allowing us to quantify informative relationships between words and pixels in an image.
Approximating CKY with Transformers
We investigate the ability of transformer models to approximate the CKY algorithm, using them to directly predict a sentence's parse and thus avoid the CKY algorithm's cubic dependence on sentence length.
How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model
Concretely, we use mechanistic interpretability techniques to explain the (limited) mathematical abilities of GPT-2 small.
