Topic
entropy
Artificial Intelligence #llm#reasoning
Independent Combinatorial Tokens Framework Boosts LLM Reasoning Performance by Up to 14.9%
Researchers propose the Independent Combinatorial Tokens (ICT) framework to resolve entropy collapse and explosion in LLM reasoning. By focusing on token-level distributional deviations using Jensen-Shannon divergence, ICT achieves average pass@4 improvement of 4.58% and up to 14.9% over baselines.
Jun 20, 2026 1 source
Artificial Intelligence #llms#reasoning
New Research Shows Chain-of-Thought Reasoning Should Be Selective, Not Default, for LLMs
A research paper on arXiv argues that chain-of-thought (CoT) reasoning should not be the default for large language models. The authors propose EDRM, a training-free routing framework that uses early decoding entropy to decide when to use CoT, achieving up to 55% token reduction and accuracy improvements across 15 benchmarks.
Jun 16, 2026 1 source