2 citations · 2 across the 4 of their papers we have counts for
4 papers
ComMer: a Framework for Compressing and Merging User Data for Personalization
Yoel Zeldes, Amir Zait, Ilia Labzovsky +2
Large Language Models (LLMs) excel at a wide range of tasks, but adapting them to new data, particularly for personalized applications, poses significant challenges due to resource…
Evidence of Cognitive Deficits andDevelopmental Advances in Generative AI: A Clock Drawing Test Analysis
Isaac R. Galatzer-Levy, Jed McGiffin, David Munday +6
Generative AI's rapid advancement sparks interest in its cognitive abilities, especially given its capacity for tasks like language understanding and code generation. This study ex…
The Cognitive Capabilities of Generative AI: A Comparative Analysis with Human Benchmarks
Isaac R. Galatzer-Levy, David Munday, Jed McGiffin +6
There is increasing interest in tracking the capabilities of general intelligence foundation models. This study benchmarks leading large language models and vision language models…
The Ability of Large Language Models to Evaluate Constraint-satisfaction in Agent Responses to Open-ended Requests
Lior Madmoni, Amir Zait, Ilia Labzovsky +1
Generative AI agents are often expected to respond to complex user requests that have No One Right Answer (NORA), e.g., "design a vegetarian meal plan below 1800 calories". Such re…