37 citations · 46 across the 15 of their papers we have counts for
5 papers · 1 filter
The Curious Case of Hallucinatory (Un)answerability: Finding Truths in the Hidden States of Over-Confident Large Language Models
Aviv Slobodkin, Omer Goldman, Avi Caciularu +2
Large language models (LLMs) have been shown to possess impressive capabilities, while also raising crucial concerns about the faithfulness of their responses. A primary issue aris…
Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew
Eylon Gueta, Omer Goldman, Reut Tsarfaty
Pre-trained language models (PLMs) have shown remarkable successes in acquiring a wide range of linguistic knowledge, relying solely on self-supervised training on text streams. Ne…
Is Probing All You Need? Indicator Tasks as an Alternative to Probing Embedding Spaces
Tal Levy, Omer Goldman, Reut Tsarfaty
The ability to identify and control different kinds of linguistic information encoded in vector representations of words has many use cases, especially for explainability and bias…
Morphological Inflection with Phonological Features
David Guriel, Omer Goldman, Reut Tsarfaty
Recent years have brought great advances into solving morphological tasks, mostly due to powerful neural models applied to various tasks as (re)inflection and analysis. Yet, such m…
Stop Uploading Test Data in Plain Text: Practical Strategies for Mitigating Data Contamination by Evaluation Benchmarks
Alon Jacovi, Avi Caciularu, Omer Goldman +1
Data contamination has become prevalent and challenging with the rise of models pretrained on large automatically-crawled corpora. For closed models, the training data becomes a tr…