7 citations · 13 across the 5 of their papers we have counts for
5 papers
Semi-Supervised Hypothesis Testing by Betting on Predictions
Yaniv Tenzer, Elad Tolochinsky, Yaniv Romano
We introduce a testing-by-betting framework that leverages predictions on unlabeled data to enhance the power of sequential hypothesis testing. Given limited samples from the joint…
Valid Best-Model Identification for LLM Evaluation via Low-Rank Factorization
Elad Tolochinsky, Yaniv Tenzer, Yaniv Romano
Selecting the best large language model (LLM) for a fixed benchmark is often expensive, since exhaustive evaluation requires running every model on every example. Multi-armed bandi…
Learning a Continue-Thinking Token for Enhanced Test-Time Scaling
Liran Ringel, Elad Tolochinsky, Yaniv Romano
Test-time scaling has emerged as an effective approach for improving language model performance by utilizing additional compute at inference time. Recent studies have shown that ov…
The UN Parallel Corpus Annotated for Translation Direction
Elad Tolochinsky, Ohad Mosafi, Ella Rabinovich +1
This work distinguishes between translated and original text in the UN protocol corpus. By modeling the problem as classification problem, we can achieve up to 95% classification a…
Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more
Elad Tolochinsky, Ibrahim Jubran, Dan Feldman
Coreset (or core-set) is a small weighted \emph{subset} of an input set with respect to a given \emph{monotonic} function that \emph{provably} a…