Records found: 7
'Framework and code to systematically compare Direct, CoT, ReAct and Reflexion agent strategies across tasks, metrics and visual analysis.'
Discover how to use Mirascope and Groq’s LLaMA 3 model to implement Chain-of-Thought reasoning, enabling AI to solve complex problems step-by-step effectively.
Fractional Reasoning introduces a model-agnostic method to adaptively control reasoning depth in LLMs, enhancing performance and efficiency on complex reasoning tasks.
‘Selective training on high-entropy tokens in LLMs improves reasoning performance and reduces computational costs, setting new benchmarks on AIME tests.’
MediaTek Research introduces Group Think, a novel token-level multi-agent paradigm that enables concurrent reasoning in large language models, significantly speeding up inference and enhancing collaborative problem-solving.
NVIDIA, CMU, and Boston University researchers introduce Nemotron-CrossThink, a novel framework that expands reinforcement learning for large language models beyond math to multiple reasoning domains with improved accuracy and efficiency.
Researchers propose DEER, a novel training-free approach allowing large reasoning language models to dynamically exit reasoning early, reducing computation and improving accuracy.