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Akhiad Bercovich

3 accepted papers

2026

Star Elastic: Many-in-One Reasoning LLMs with Efficient Budget Control

ICML 2026poster

Training a family of large language models (LLMs), either from scratch or via iterative compression, is prohibitively expensive and inefficient, requiring separate training runs for each model in the family. In this paper, we introduce Star Elastic, a novel LLM post-training method that adds N neste…

Cited by 0SourceScholar
2025

FFN Fusion: Rethinking Sequential Computation in Large Language Models

NeurIPS 2025spotlight

We introduce \textit{FFN Fusion}, an architectural optimization technique that reduces sequential computation in large language models by identifying and exploiting natural opportunities for parallelization. Our key insight is that sequences of Feed-Forward Network (FFN) layers, particularly those r…

Cited by 0SourceScholar
2025

Puzzle: Distillation-Based NAS for Inference-Optimized LLMs

ICML 2025poster

Large language models (LLMs) offer remarkable capabilities, yet their high inference costs restrict wider adoption. While increasing parameter counts improves accuracy, it also broadens the gap between state-of-the-art capabilities and practical deployability. We present **Puzzle**, a hardware-aware…

Cited by 2SourcePDFScholar