😎 A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, Agent, and Beyond
Qwen3.8-27B on RTX 5090 Laptop 24GB — TWIN-TURBO NVFP4 (native llama.cpp) vs Coder390 Q3 LynnStyle (.ninfer + NInfer engine in WSL2/Docker): 86 tok/s decode, 262K context, C4 aggregate 228 tok/s. Every number a controlled measurement.
AVR: Learning Adaptive Reasoning Paths for Efficient Visual Reasoning
[ICLR 2026] FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoning
Training-free contrastive decoding for efficient LLM reasoning: shorter chain-of-thought (CoT), less overthinking, and fewer reasoning tokens.
反内耗 Skill：把反复想、纠结、脑内循环拆解成具体问题，判断是否值得继续思考、现在能否行动、继续想能否产生新信息。
Independent replication and extension of MIT CSAIL's "Sparks of Weight-Space Programming" on Qwen3.5-0.8B: rebuilt loop edit, truth-gated reflex in 16 MLP neurons, pre-registered tests of knowing vs. committing. Report v0.3 (EN/DE), code, data, pre-registration log.
TED-style presentation about Overthinking built with PptxGenJS — by Mohamed Gharieb
高N人脑内防沉迷系统 · A prompt-only workflow for High-N overthinkers: reality check, then CET-6 vocabulary. MBTI here is a metaphor, not a diagnosis.
A structured AI prompt for sorting thoughts, reducing overthinking, and separating facts, interpretations, fears, and hopes.
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