14 citations · 31 across the 20 of their papers we have counts for
8 papers · 1 filter
EventFull: Complete and Consistent Event Relation Annotation
Alon Eirew, Eviatar Nachshoni, Aviv Slobodkin +1
Event relation detection is a fundamental NLP task, leveraged in many downstream applications, whose modeling requires datasets annotated with event relations of various types. How…
GRADE: Quantifying Sample Diversity in Text-to-Image Models
Royi Rassin, Aviv Slobodkin, Shauli Ravfogel +2
We introduce GRADE, an automatic method for quantifying sample diversity in text-to-image models. Our method leverages the world knowledge embedded in large language models and vis…
Explicating the Implicit: Argument Detection Beyond Sentence Boundaries
Paul Roit, Aviv Slobodkin, Eran Hirsch +4
Detecting semantic arguments of a predicate word has been conventionally modeled as a sentence-level task. The typical reader, however, perfectly interprets predicate-argument rela…
Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models
Nitzan Bitton-Guetta, Aviv Slobodkin, Aviya Maimon +6
Imagine observing someone scratching their arm; to understand why, additional context would be necessary. However, spotting a mosquito nearby would immediately offer a likely expla…
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…
The Power of Summary-Source Alignments
Ori Ernst, Ori Shapira, Aviv Slobodkin +5
Multi-document summarization (MDS) is a challenging task, often decomposed to subtasks of salience and redundancy detection, followed by text generation. In this context, alignment…
Multi-Review Fusion-in-Context
Aviv Slobodkin, Ori Shapira, Ran Levy +1
Grounded text generation, encompassing tasks such as long-form question-answering and summarization, necessitates both content selection and content consolidation. Current end-to-e…
Attribute First, then Generate: Locally-attributable Grounded Text Generation
Aviv Slobodkin, Eran Hirsch, Arie Cattan +2
Recent efforts to address hallucinations in Large Language Models (LLMs) have focused on attributed text generation, which supplements generated texts with citations of supporting…