1 citations · 2 across the 10 of their papers we have counts for
11 papers
Brain-IT-VQA: From Brain Signals to Answers
Roman Beliy, Matias Cosarinsky, Oliver Heinimann +2
Decoding visual content from fMRI signals recorded while a person views images, and specifically answering questions about the seen images, is a long-standing challenge. While sign…
From Activation to Specificity: Automating Counterfactual Testing of Visual Representations in the Human Brain
Yuval Golbari, Navve Wasserman, Matias Cosarinsky +5
Identifying which brain regions represent a visual concept in the human brain is a central challenge in neuroscience. Existing approaches have localized coarse functional regions (…
BrainExplore: Large-Scale Discovery of Interpretable Visual Representations in the Human Brain
Navve Wasserman, Matias Cosarinsky, Yuval Golbari +4
Understanding how the human brain represents visual concepts, and in which brain regions these representations are encoded, remains a long-standing challenge. Decades of work have…
Brain-IT: Image Reconstruction from fMRI via Brain-Interaction Transformer
Roman Beliy, Amit Zalcher, Jonathan Kogman +2
Reconstructing images seen by people from their fMRI brain recordings provides a non-invasive window into the human brain. Despite recent progress enabled by diffusion models, curr…
ImpMIA: Leveraging Implicit Bias for Membership Inference Attack
Yuval Golbari, Navve Wasserman, Gal Vardi +1
Determining which data samples were used to train a model, known as Membership Inference Attack (MIA), is a well-studied and important problem with implications on data privacy. So…
DocReRank: Single-Page Hard Negative Query Generation for Training Multi-Modal RAG Rerankers
Navve Wasserman, Oliver Heinimann, Yuval Golbari +3
Rerankers play a critical role in multimodal Retrieval-Augmented Generation (RAG) by refining ranking of an initial set of retrieved documents. Rerankers are typically trained usin…
Don't Judge Before You CLIP: A Unified Approach for Perceptual Tasks
Amit Zalcher, Navve Wasserman, Roman Beliy +2
Visual perceptual tasks aim to predict human judgment of images (e.g., emotions invoked by images, image quality assessment). Unlike objective tasks such as object/scene recognitio…
REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark
Navve Wasserman, Roi Pony, Oshri Naparstek +4
Accurate multi-modal document retrieval is crucial for Retrieval-Augmented Generation (RAG), yet existing benchmarks do not fully capture real-world challenges with their current d…
The Wisdom of a Crowd of Brains: A Universal Brain Encoder
Roman Beliy, Navve Wasserman, Amit Zalcher +1
Image-to-fMRI encoding is important for both neuroscience research and practical applications. However, such "Brain-Encoders" have been typically trained per-subject and per fMRI-d…
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
Navve Wasserman, Noam Rotstein, Roy Ganz +1
Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual ins…
Functional Brain-to-Brain Transformation with No Shared Data
Navve Wasserman, Roman Beliy, Roy Urbach +1
Combining Functional MRI (fMRI) data across different subjects and datasets is crucial for many neuroscience tasks. Relying solely on shared anatomy for brain-to-brain mapping is i…