#llm-budgeting News & Analysis

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

2 articles

AINeutralarXiv – CS AI · Jun 236/10

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DART: Draft-Agreement Routing for Training-Free Adaptive Thinking Budgets in Hybrid Reasoning Models

Researchers introduce DART, a training-free routing framework that dynamically allocates computational thinking budgets in hybrid reasoning models by sampling cheap draft responses and using agreement patterns to decide between direct answers and extended reasoning. The approach achieves significant accuracy improvements on math and code tasks while reducing token consumption by 15-69%, without requiring labeled data or model fine-tuning.

AINeutralarXiv – CS AI · Jun 96/10

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Agentic Search for Counterfactual Recourse under Fixed LLM Budgets

Researchers propose Comp-MCTS, an AI framework that efficiently generates multiple counterfactual explanations under limited LLM budget constraints by using tree-search algorithms to allocate queries toward novel intervention directions. The approach demonstrates superior performance in producing diverse, validated counterfactuals compared to existing single-candidate and multi-candidate baselines on real-world datasets.