28 citations · 37 across the 12 of their papers we have counts for
4 papers · 1 filter
GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation
Hao Liu, Guangyan Li, Wensheng Zhang +1
Large Language Models (LLMs) exhibit strong reasoning abilities, but their high computational costs limit their practical deployment. Recent studies reveal significant redundancy i…
Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback
Kyuyoung Kim, Ah Jeong Seo, Hao Liu +2
Large language models (LLMs) fine-tuned with alignment techniques, such as reinforcement learning from human feedback, have been instrumental in developing some of the most capable…
CriticBench: Benchmarking LLMs for Critique-Correct Reasoning
Zicheng Lin, Zhibin Gou, Tian Liang +3
The ability of Large Language Models (LLMs) to critique and refine their reasoning is crucial for their application in evaluation, feedback provision, and self-improvement. This pa…
ChipNeMo: Domain-Adapted LLMs for Chip Design
Mingjie Liu, Teodor-Dumitru Ene, Robert Kirby +39
ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we…