评估LLM代理在预算约束下的经济决策，揭示资源效率与任务完成度的平衡新基准。
arXiv:2608.05519v1 Announce Type: new Abstract: Agent benchmarks usually measure task completion and treat resource use as an auxiliary statistic. In …
多模态大模型的空间推理可解释性与资源效率新方法，助力机器人等决策关键场景提升信任与审计能力
arXiv:2607.27145v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) are increasingly deployed in decision-critical pipelines s…
提出用统计方法为推理模型设计早停策略，显著提升计算效率而不损失准确度。
arXiv:2602.13935v2 Announce Type: replace-cross Abstract: While LLMs have seen substantial improvement in reasoning capabilities, they also sometimes …
用本体论抽象现实，探索降低LLM资源消耗的新思路，让大模型在CPU上飞驰
# A Wild Idea: Abstract Reality with Ontology ## Background Large language models (LLMs) debuted with GPT-3 back in June 2020. After roughly five to s…
数十亿token投入AI坦克训练，是技术探索还是资源浪费？令人好奇的背后真相。
Article URL: https://old.reddit.com/r/vibecoding/comments/1tqtl2l/people_have_spent_billions_of_tokens_training_ai/ Comments URL: https://news.ycombin…
MoE架构在严格等资源条件下首次证明超越稠密大模型，ICLR 2026最新研究。
arXiv:2506.12119v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) language models dramatically expand model capacity and achieve remarkable…