19 citations · 71 across the 35 of their papers we have counts for
38 papers
StructSim: Measuring Idea Similarity at Scale Through Structural Representation
Yaqing Yang, Yaqing yang, Vikram Mohanty +4
Measuring idea similarity is fundamental to creativity evaluation, especially as LLMs enable idea generation at increasing scale. However, text embeddings collapse an idea into a s…
ProteinJEPA: Latent prediction improves protein language model pretraining
Dan Ofer, Dafna Shahaf, Michal Linial
Protein language models are trained primarily with masked language modeling (MLM), which predicts masked amino-acid identities. Joint-embedding predictive architectures (JEPA) inst…
LLMs versus the Halting Problem: Characterizing Program Termination Reasoning
Oren Sultan, Jordi Armengol-Estape, Pascal Kesseli +4
Determining whether a program terminates is a central problem in computer science. Turing's Halting Problem established termination as undecidable, showing that no algorithm can un…
Finding your MUSE: Mining Unexpected Solutions Engine
Nir Sweed, Hanit Hakim, Ben Wolfson +2
Innovators often exhibit cognitive fixation on existing solutions or nascent ideas, hindering the exploration of novel alternatives. This paper introduces a methodology for constru…
One Joke to Rule them All? On the (Im)possibility of Generalizing Humor
Mor Turgeman, Chen Shani, Dafna Shahaf
Humor is a broad and complex form of communication that remains challenging for machines. Despite its broadness, most existing research on computational humor traditionally focused…
Reliable Proof Generation with LLMs via Analogical Retrieval and Symbolic Verification: A Case Study in Euclidean Geometry
Oren Sultan, Eitan Stern, Dafna Shahaf
Large language models (LLMs) struggle with formal domains that require rigorous logical deduction and symbolic reasoning, such as mathematical proof generation. We propose a neuro-…