activity
20222025
most citedTRUE: Re-evaluating Factual Consistency Evaluation

13 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

RefVNLI: Towards Scalable Evaluation of Subject-driven Text-to-image Generation

Aviv Slobodkin, Hagai Taitelbaum, Yonatan Bitton +7

Subject-driven text-to-image (T2I) generation aims to produce images that align with a given textual description, while preserving the visual identity from a referenced subject ima…

cs.CL2025

On Reference (In-)Determinacy in Natural Language Inference

Sihao Chen, Chaitanya Malaviya, Alex Fabrikant +4

We revisit the reference determinacy (RD) assumption in the task of natural language inference (NLI), i.e., the premise and hypothesis are assumed to refer to the same context when…

cs.CV2024

KITTEN: A Knowledge-Intensive Evaluation of Image Generation on Visual Entities

Hsin-Ping Huang, Xinyi Wang, Yonatan Bitton +8

Recent advances in text-to-image generation have improved the quality of synthesized images, but evaluations mainly focus on aesthetics or alignment with text prompts. Thus, it rem…

cs.IR2022★ 4 cited

A Dataset for Sentence Retrieval for Open-Ended Dialogues

Itay Harel, Hagai Taitelbaum, Idan Szpektor +1

We address the task of sentence retrieval for open-ended dialogues. The goal is to retrieve sentences from a document corpus that contain information useful for generating the next…

cs.CL2022★ 13 cited

TRUE: Re-evaluating Factual Consistency Evaluation

Or Honovich, Roee Aharoni, Jonathan Herzig +7

Grounded text generation systems often generate text that contains factual inconsistencies, hindering their real-world applicability. Automatic factual consistency evaluation may h…