Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models
PositiveArtificial Intelligence
- Recent research highlights the challenges of pruning reasoning language models (RLMs) like OpenAI's o1 and DeepSeek
- This development is significant as it underscores the need for innovative pruning techniques tailored specifically for RLMs, which are essential for efficient deployment in resource
- The findings reflect a broader trend in AI research, where balancing model efficiency with performance remains a critical issue. As models become more complex, the risk of overthinking and redundant reasoning steps emerges, necessitating new strategies to optimize their functionality while maintaining accuracy.
— via World Pulse Now AI Editorial System





