1 citations · 1 across the 8 of their papers we have counts for
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Skill Issue: Are Skills Language-Invariant in LLMs?
Bobby Cheng, Adam Gaber, Zhengyuan Liu +4
Large language models access knowledge inconsistently across languages, but to what extent do they differ in their skill sets when interacting with different languages? This work q…
MameLoshnLM: Yiddish Language Model and Evaluation Benchmark
Uri Katz, Omer Goldman, Tomasz Limisiewicz +2
We present MameLoshnLM, the first open-source 8B-parameter language model built specifically for Yiddish. Despite Yiddish's rich textual tradition, its limited digital presence and…
Location Not Found: Exposing Implicit Local and Global Biases in Multilingual LLMs
Guy Mor-Lan, Omer Goldman, Matan Eyal +6
Multilingual large language models (LLMs) have minimized the fluency gap between languages. This advancement, however, exposes models to the risk of biased behavior, as knowledge a…
ECLeKTic: a Novel Challenge Set for Evaluation of Cross-Lingual Knowledge Transfer
Omer Goldman, Uri Shaham, Dan Malkin +11
To achieve equitable performance across languages, large language models (LLMs) must be able to abstract knowledge beyond the language in which it was learnt. However, the current…
Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP
Omer Goldman, Alon Jacovi, Aviv Slobodkin +3
Improvements in language models' capabilities have pushed their applications towards longer contexts, making long-context evaluation and development an active research area. Howeve…
Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance
Omer Goldman, Avi Caciularu, Matan Eyal +3
Despite it being the cornerstone of BPE, the most common tokenization algorithm, the importance of compression in the tokenization process is still unclear. In this paper, we argue…