565 citations · 580 across the 12 of their papers we have counts for
13 papers
Cross-Lingual Exploration for Parametric Knowledge
Elisha Diskind, Itamar Trainin, Uri Shaham +3
Parametric knowledge in Large Language Models is not equally accessible across languages. As a result, standard inference techniques often struggle to surface localized facts, lead…
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…
CoverBench: A Challenging Benchmark for Complex Claim Verification
Alon Jacovi, Moran Ambar, Eyal Ben-David +5
There is a growing line of research on verifying the correctness of language models' outputs. At the same time, LMs are being used to tackle complex queries that require reasoning.…
Multilingual Instruction Tuning With Just a Pinch of Multilinguality
Uri Shaham, Jonathan Herzig, Roee Aharoni +3
As instruction-tuned large language models (LLMs) gain global adoption, their ability to follow instructions in multiple languages becomes increasingly crucial. In this work, we in…
ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding
Uri Shaham, Maor Ivgi, Avia Efrat +2
We introduce ZeroSCROLLS, a zero-shot benchmark for natural language understanding over long texts, which contains only test and small validation sets, without training data. We ad…
Causes and Cures for Interference in Multilingual Translation
Uri Shaham, Maha Elbayad, Vedanuj Goswami +2
Multilingual machine translation models can benefit from synergy between different language pairs, but also suffer from interference. While there is a growing number of sophisticat…
Efficient Long-Text Understanding with Short-Text Models
Maor Ivgi, Uri Shaham, Jonathan Berant
Transformer-based pretrained language models (LMs) are ubiquitous across natural language understanding, but cannot be applied to long sequences such as stories, scientific article…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
Instruction Induction: From Few Examples to Natural Language Task Descriptions
Or Honovich, Uri Shaham, Samuel R. Bowman +1
Large language models are able to perform a task by conditioning on a few input-output demonstrations - a paradigm known as in-context learning. We show that language models can ex…
SCROLLS: Standardized CompaRison Over Long Language Sequences
Uri Shaham, Elad Segal, Maor Ivgi +8
NLP benchmarks have largely focused on short texts, such as sentences and paragraphs, even though long texts comprise a considerable amount of natural language in the wild. We intr…
What Do You Get When You Cross Beam Search with Nucleus Sampling?
Uri Shaham, Omer Levy
We combine beam search with the probabilistic pruning technique of nucleus sampling to create two deterministic nucleus search algorithms for natural language generation. The first…
Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language
Avia Efrat, Uri Shaham, Dan Kilman +1
Current NLP datasets targeting ambiguity can be solved by a native speaker with relative ease. We present Cryptonite, a large-scale dataset based on cryptic crosswords, which is bo…
Neural Machine Translation without Embeddings
Uri Shaham, Omer Levy
Many NLP models operate over sequences of subword tokens produced by hand-crafted tokenization rules and heuristic subword induction algorithms. A simple universal alternative is t…