565 citations · 734 across the 71 of their papers we have counts for
21 papers · 1 filter
Performance Gap in Entity Knowledge Extraction Across Modalities in Vision Language Models
Ido Cohen, Daniela Gottesman, Mor Geva +1
Vision-language models (VLMs) excel at extracting and reasoning about information from images. Yet, their capacity to leverage internal knowledge about specific entities remains un…
Inferring Functionality of Attention Heads from their Parameters
Amit Elhelo, Mor Geva
Attention heads are one of the building blocks of large language models (LLMs). Prior work on investigating their operation mostly focused on analyzing their behavior during infere…
Do Large Language Models Perform Latent Multi-Hop Reasoning without Exploiting Shortcuts?
Sohee Yang, Nora Kassner, Elena Gribovskaya +2
We evaluate how well Large Language Models (LLMs) latently recall and compose facts to answer multi-hop queries like "In the year Scarlett Johansson was born, the Summer Olympics w…
Eliciting Textual Descriptions from Representations of Continuous Prompts
Dana Ramati, Daniela Gottesman, Mor Geva
Continuous prompts, or "soft prompts", are a widely-adopted parameter-efficient tuning strategy for large language models, but are often less favorable due to their opaque nature.…
Language Models Encode Numbers Using Digit Representations in Base 10
Amit Arnold Levy, Mor Geva
Large language models (LLMs) frequently make errors when handling even simple numerical problems, such as comparing two small numbers. A natural hypothesis is that these errors ste…
Towards Interpreting Visual Information Processing in Vision-Language Models
Clement Neo, Luke Ong, Philip Torr +3
Vision-Language Models (VLMs) are powerful tools for processing and understanding text and images. We study the processing of visual tokens in the language model component of LLaVA…