419 citations · 3.1k across the 71 of their papers we have counts for
72 papers
Contextual Plackett-Luce: An Efficient Neural Model for Probabilistic Sequence Selection under Ambiguity
Noam Mizrachi, Nadav Har-Tuv, Shai Shalev-Shwartz
Selecting a coherent sequence or subset of elements is a fundamental problem in structured prediction, arising in tasks such as detection, trajectory forecasting, and representativ…
From Reasoning to Super-Intelligence: A Search-Theoretic Perspective
Shai Shalev-Shwartz, Amnon Shashua
Chain-of-Thought (CoT) reasoning has emerged as a powerful tool for enhancing the problem-solving capabilities of large language models (LLMs). However, the theoretical foundations…
FormulaOne: Measuring the Depth of Algorithmic Reasoning Beyond Competitive Programming
Gal Beniamini, Yuval Dor, Alon Vinnikov +10
Frontier AI models demonstrate formidable breadth of knowledge. But how close are they to true human -- or superhuman -- expertise? Genuine experts can tackle the hardest problems…
Artificial Expert Intelligence through PAC-reasoning
Shai Shalev-Shwartz, Amnon Shashua, Gal Beniamini +6
Artificial Expert Intelligence (AEI) seeks to transcend the limitations of both Artificial General Intelligence (AGI) and narrow AI by integrating domain-specific expertise with cr…
Untangling Lariats: Subgradient Following of Variationally Penalized Objectives
Kai-Chia Mo, Shai Shalev-Shwartz, Nisæl Shártov
We describe an apparatus for subgradient-following of the optimum of convex problems with variational penalties. In this setting, we receive a sequence and seek a…
Jamba: A Hybrid Transformer-Mamba Language Model
Opher Lieber, Barak Lenz, Hofit Bata +19
We present Jamba, a new base large language model based on a novel hybrid Transformer-Mamba mixture-of-experts (MoE) architecture. Specifically, Jamba interleaves blocks of Transfo…