Weizmann Institute of Science

Selected work

Representative Papers

Scheduling With Time Discounts

Feb 13, 2024

This paper studies the online weighted task scheduling problem with time-decaying values in financial settings, where future rewards are discounted at rate δ ∈ [0,1) and arrivals are uncertain; the objective is to maximize the total present value. We propose the first deterministic memoryless algorithm that is optimal for δ ≤ 0.77 and prove its competitive ratio matches the theoretical upper bound for this class of algorithms. Furthermore, we design a randomized algorithm that strictly surpasses the deterministic competitive ratio upper bound—thereby completing the precise characterization of the competitive ratio for discounted scheduling. Our theoretical results are directly applicable to real-world financial systems, such as blockchain transaction scheduling, and provide a unified modeling framework and provably optimal algorithms for online resource allocation under discounted utility.

6 citationsRead paper

Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies

Jan 31, 2025arXiv.org

To address the slow inference speed of large language models (LLMs) and the limitation of existing speculative decoding methods—namely, their reliance on shared vocabularies—this paper proposes the first lossless speculative decoding framework supporting heterogeneous tokenizers. Methodologically, it requires no vocabulary alignment, modifies or retrains neither the draft nor the target model, and achieves cross-vocabulary distribution preservation via three lightweight components: token mapping, dynamic probability projection, and distribution calibration. Its core contribution is the elimination of vocabulary consistency constraints, enabling the first truly plug-and-play speculative decoding across disparate tokenizers. Evaluated on summarization, code generation, and long-context tasks, the framework achieves average speedups of 1.8–2.3× over standard autoregressive decoding, with zero accuracy degradation—outperforming all baseline speculative decoding approaches.

3 citations1 influentialRead paper

The Oracle Complexity of Simplex-based Matrix Games: Linear Separability and Nash Equilibria

Dec 09, 2024arXiv.org

This paper studies the oracle complexity of matrix games $max_{mathbf{w}inmathcal{W}}min_{mathbf{p}inDelta}mathbf{p}^ op Amathbf{w}$ under simplex constraints, focusing on linear separability testing and $varepsilon$-approximate Nash equilibrium computation in zero-sum games. Within the Nemirovski–Yudin oracle framework, we establish the first tight lower bounds for both single- and double-sided matrix-vector multiplication oracles. For linear separability with margin $gamma_a$, we prove an $Omega(gamma_a^{-2})$ lower bound for single-sided queries—matching the Perceptron algorithm’s rate—and a $widetilde{Omega}(gamma_a^{-2/3})$ lower bound under double-sided access, demonstrating inherent limitations of acceleration. For Nash equilibrium approximation, we improve the prior best lower bound to $widetilde{Omega}(varepsilon^{-2/5})$, achieving an exponential improvement over previous results. Our key technical innovation is an $ell_1$-geometry-adapted analysis, which enables the first tight oracle complexity lower bounds for double-sided matrix multiplication.

2 citationsRead paper

Types for Grassroots Logic Programs

Jan 25, 2026

Existing Grassroots Logic Programs (GLPs) lack type support for interactive, potentially deadlocking, or non-terminating computations, making it difficult to ensure communication reliability in AI-assisted development. This work proposes the first modal path regular type system incorporating directional modes, which distinguishes between read and write directions of subterms to enable static type checking for partial, interactive, and even non-terminating programs. By integrating covariance and contravariance semantic conditions with formal syntactic rules, the system establishes that well-typedness is equivalent to semantic paths satisfying directional constraints. Furthermore, a correct-by-construction Dart implementation is automatically generated from the formal specification by an AI, demonstrating the feasibility of human-AI collaborative programming.

1 citationsRead paper

Grassroots Consensus

May 25, 2025

Existing consensus protocols inadequately address the needs of grassroots digital platforms—such as sovereign democratic communities and community banks—for lightweight, efficient, and decentralized agreement mechanisms. Method: We propose a novel blockchain consensus protocol tailored for digital social contracts, built upon the blocklace data structure. It uniquely embeds constitutional rules and amendment procedures directly into the consensus layer, enabling decentralized modeling of social contracts. The protocol integrates UDP-based transport optimization and fault-tolerant algorithms designed for partially synchronous networks. Contribution/Results: Our design achieves silence-optimality, strong responsiveness, cross-throughput efficiency, and grassroots deployability. It outperforms state-of-the-art protocols under both low- and high-throughput regimes while maintaining simplicity and scalability. To our knowledge, this is the first consensus protocol to unify institutional programmability, network adaptability, and grassroots deployability at the consensus layer.

1 citationsRead paper

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