17 citations · 20 across the 5 of their papers we have counts for
6 papers
Cross-Prompt Inference Mitigates Rare-Class Suppression in Imbalanced VLM Finetuning
Emanuel Ben Baruch, Sivan Biham, Alon Shoshan +2
When a vision-language model is finetuned on class-imbalanced data, rare-class recall can fall well below the model's own zero-shot performance. In this regime, we uncover a surpri…
Propose and Attend: Training-free MLLM Grounding Confidence via Multi-Token Localized Attention
Daniel Shalam, Emanuel Ben Baruch, Avi Ben Cohen +1
Multimodal large language models can emit localized predictions, bounding boxes for objects and temporal windows for video and audio events, but they hallucinate these regions prol…
TrajLoc: Trajectory-Attention Localization for Multi-Object Motion Control
Omer Sela, Inbar Huberman-Spiegelglas, Michael Rotman +2
Controlling the motion of multiple objects in image-to-video (I2V) generation requires preserving object identities while enforcing adherence to distinct target trajectories. This…
Planar-SfM: Camera Pose Estimation via Homography Graph Embeddings
Gabi Pragier, Matan Karklinsky, David Ungarish +1
Structure from Motion (SfM) systems traditionally struggle with planar scenes, where standard epipolar geometry-based methods become degenerate. Rather than viewing planar surfaces…
It's All in the Head: Representation Knowledge Distillation through Classifier Sharing
Emanuel Ben-Baruch, Matan Karklinsky, Yossi Biton +3
Representation knowledge distillation aims at transferring rich information from one model to another. Common approaches for representation distillation mainly focus on the direct…
ML-Decoder: Scalable and Versatile Classification Head
Tal Ridnik, Gilad Sharir, Avi Ben-Cohen +2
In this paper, we introduce ML-Decoder, a new attention-based classification head. ML-Decoder predicts the existence of class labels via queries, and enables better utilization of…