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1. [2401.08092v1] A Survey of Resource-efficient LLM and Multimodal Foundation Models

   Resource-efficient LLMs and Multimodal Models
   
   A useful survey of resource-efficient LLMs and multimodal foundations models.
   
   Provides a comprehensive analysis and insights into ML efficiency research, including architectures, algorithms, and practical system designs and implementations.

   2024-01-28 Tags: llm, efficiency, survey paper, raspberry pi, self-hosted by klotz
2. A Comprehensive Survey of Large Language Models (LLMs)

   - Three Emergent Abilities for LLMs are In-Context Learning (ICL), Instruction Following & Step-By-Step Reasoning (CoT).
   - Key Practices related to LLMs are: Scaling, Training, Ability Eliciting, Alignment Tuning, Tools.
   - Adaption Of LLMs include: Instruction Tuning, Alignment Tuning, Memory-Efficient Model Adaptation, etc.
   - Prompt Engineering: In-Context Learning, Chain-Of-Thought, Planning.
   - ICL Prompt Engineering Implementations: KATE, EPR, SG-ICL, APE, Structured Prompting, GlobalE & LocalE.
   - CoT Prompt Engineering Implementations: Complex CoT, Auto-CoT, Selection-Inference, Self-consistency, DIVERSE, Rationale-augmented ensembles.
   - Planning Prompt Engineering Implementations: Least-to-most prompting, DECOMP, PS, Faithful CoT, PAL, HuggingGPT, AdaPlanner, TIP, RAP, ChatCoT, ReAct, Reflexion, Tree of Thoughts.

   2023-12-14 Tags: llm, survey paper by klotz
3. On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data

   2018-09-18 Tags: anomaly detection, survey paper, arxiv by klotz
4. On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data - Semantic Scholar

   2018-09-18 Tags: anomaly detection, survey paper, semanticscholar by klotz

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