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Found 3 papers, 1 papers with code
Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization
To address this, we propose a novel two-stage framework for adaptive and efficient reasoning.
O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning
Experiments on various mathematical reasoning benchmarks show that O1-Pruner not only significantly reduces inference overhead but also achieves higher accuracy, providing a novel and promising solution to this challenge.
Patch Matters: Training-free Fine-grained Image Caption Enhancement via Local Perception
Our method first divides the image into semantic and spatial patches to extract fine-grained details, enhancing the model's local perception of the image.
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