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#token-cost News & Analysis

2 articles tagged with #token-cost. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AIBullisharXiv – CS AI · May 97/10
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Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost

Researchers introduce Post-Reasoning, a technique that improves LLM performance by having models justify answers after generating final responses, without increasing latency or token costs. The method demonstrates 17.37% mean performance improvements across 117 model-benchmark settings and establishes a new efficiency frontier for direct-answer AI capabilities.

AIBullisharXiv – CS AI · Jun 96/10
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Larch: Learned Query Optimization for Semantic Predicates

Larch is a new optimization framework that improves the efficiency of semantic SQL queries by reducing token usage and computational costs when processing unstructured data with Large Language Models. The framework uses two approaches—reinforcement learning and supervised learning—to optimize the order of filter evaluation, achieving 3x-19x token cost reductions compared to existing solutions.