2 citations · 2 across the 6 of their papers we have counts for
9 papers
Phonological Interference in Multilingual Speech Models
Moran Yanuka, Raja Giryes, Morris Alper +1
Phoneme-level models transcribe or generate speech as a sequence of phonemes, the smallest sound units that distinguish words. These models enable fine-grained pronunciation contro…
NAMESAKES: Probing Identity Memorization in Text-to-Image Models
Morris Alper, Vasudha Varadarajan, Moran Yanuka +2
Text-to-image (T2I) models generate realistic likenesses of some individuals when prompted with their names, raising privacy concerns. However, distinguishing whether a generated f…
ID-LoRA: Identity-Driven Audio-Video Personalization with In-Context LoRA
Aviad Dahan, Moran Yanuka, Noa Kraicer +2
Existing video personalization methods preserve visual likeness but treat video and audio separately. Without access to the visual scene, audio models cannot synchronize sounds wit…
Principled Coarse-Grained Acceptance for Speculative Decoding in Speech
Moran Yanuka, Paul Dixon, Eyal Finkelshtein +2
Speculative decoding accelerates autoregressive speech generation by letting a fast draft model propose tokens that a larger target model verifies. However, for speech LLMs that ge…
ConlangCrafter: Constructing Languages with a Multi-Hop LLM Pipeline
Morris Alper, Moran Yanuka, Raja Giryes +1
Constructed languages (conlangs) such as Esperanto and Quenya have played diverse roles in art, philosophy, and international communication. Meanwhile, foundation models have revol…
EditInspector: A Benchmark for Evaluation of Text-Guided Image Edits
Ron Yosef, Moran Yanuka, Yonatan Bitton +1
Text-guided image editing, fueled by recent advancements in generative AI, is becoming increasingly widespread. This trend highlights the need for a comprehensive framework to veri…
Bridging the Visual Gap: Fine-Tuning Multimodal Models with Knowledge-Adapted Captions
Moran Yanuka, Assaf Ben Kish, Yonatan Bitton +2
Recent research increasingly focuses on training vision-language models (VLMs) with long, detailed image captions. However, small-scale VLMs often struggle to balance the richness…
ICC: Quantifying Image Caption Concreteness for Multimodal Dataset Curation
Moran Yanuka, Morris Alper, Hadar Averbuch-Elor +1
Web-scale training on paired text-image data is becoming increasingly central to multimodal learning, but is challenged by the highly noisy nature of datasets in the wild. Standard…
Mitigating Open-Vocabulary Caption Hallucinations
Assaf Ben-Kish, Moran Yanuka, Morris Alper +2
While recent years have seen rapid progress in image-conditioned text generation, image captioning still suffers from the fundamental issue of hallucinations, namely, the generatio…