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Scalable Chain of Thoughts via Elastic Reasoning
Manage episode 483179306 series 3448051
In this week's episode, we talk about Elastic Reasoning, a novel framework designed to enhance the efficiency and scalability of large reasoning models by explicitly separating the reasoning process into two distinct phases: thinking and solution.
This separation allows for independent allocation of computational budgets, addressing challenges related to uncontrolled output lengths in real-world deployments with strict resource constraints.
Our discussion explores how Elastic Reasoning contributes to more concise and efficient reasoning, even in unconstrained settings, and its implications for deploying LRMs in resource-limited environments.
Read the paper here: https://arxiv.org/pdf/2505.05315
Sign up for the next discussion & see more AI research: arize.com/ai-research-papers
Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.
50 قسمت
Manage episode 483179306 series 3448051
In this week's episode, we talk about Elastic Reasoning, a novel framework designed to enhance the efficiency and scalability of large reasoning models by explicitly separating the reasoning process into two distinct phases: thinking and solution.
This separation allows for independent allocation of computational budgets, addressing challenges related to uncontrolled output lengths in real-world deployments with strict resource constraints.
Our discussion explores how Elastic Reasoning contributes to more concise and efficient reasoning, even in unconstrained settings, and its implications for deploying LRMs in resource-limited environments.
Read the paper here: https://arxiv.org/pdf/2505.05315
Sign up for the next discussion & see more AI research: arize.com/ai-research-papers
Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.
50 قسمت
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