565 citations · 734 across the 71 of their papers we have counts for
19 papers · 2 filters
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.…
CoverBench: A Challenging Benchmark for Complex Claim Verification
Alon Jacovi, Moran Ambar, Eyal Ben-David +5
There is a growing line of research on verifying the correctness of language models' outputs. At the same time, LMs are being used to tackle complex queries that require reasoning.…
When Can Transformers Count to n?
Gilad Yehudai, Haim Kaplan, Guy Dar +4
Large language models based on the transformer architecture can solve highly complex tasks, yet their fundamental limitations on simple algorithmic problems remain poorly understoo…