1 citations · 1 across the 8 of their papers we have counts for
9 papers
TANGO: Watermarking Masked Diffusion Language Models in Token Pairs
Kasra Arabi, Nir Weinberger, Micah Goldblum +1
Masked-diffusion language models fill in masked positions in parallel and in no fixed order. Most practical text watermarks assume left-to-right generation. They key each token to…
Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts
Ilay Yavlovich, Jad Agbaria, Muhamed Mhamed +2
The Linear Assignment Problem is a fundamental combinatorial optimization task where classical exact solvers ensure optimality but suffer from an bottleneck, w…
Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings
Sreejith Sreekumar, Nir Weinberger
Maximum likelihood prediction (MLP) is a core task at the heart of modern large language models. Here, we study a quantum version of this task for a simplified data model consistin…
Exploration-Exploitation Tradeoff in Universal Lossy Compression
Nir Weinberger, Ram Zamir
Universal compression can learn the source and adapt to it either in a batch mode (forward adaptation), or in a sequential mode (backward adaptation). We recast the sequential mode…
When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets
Chen Zeno, Hila Manor, Greg Ongie +3
While diffusion models generate high-quality images via probability flow, the theoretical understanding of this process remains incomplete. A key question is when probability flow…
A representation-learning game for classes of prediction tasks
Neria Uzan, Nir Weinberger
We propose a game-based formulation for learning dimensionality-reducing representations of feature vectors, when only a prior knowledge on future prediction tasks is available. In…
Statistical curriculum learning: An elimination algorithm achieving an oracle risk
Omer Cohen, Ron Meir, Nir Weinberger
We consider a statistical version of curriculum learning (CL) in a parametric prediction setting. The learner is required to estimate a target parameter vector, and can adaptively…
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting -- An Analytical Model
Daniel Goldfarb, Itay Evron, Nir Weinberger +2
In continual learning, catastrophic forgetting is affected by multiple aspects of the tasks. Previous works have analyzed separately how forgetting is affected by either task simil…
How do Minimum-Norm Shallow Denoisers Look in Function Space?
Chen Zeno, Greg Ongie, Yaniv Blumenfeld +2
Neural network (NN) denoisers are an essential building block in many common tasks, ranging from image reconstruction to image generation. However, the success of these models is n…