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Linkedin - Grounding Techniques for LLMs - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Linkedin - Grounding Techniques for LLMs (/Thread-Linkedin-Grounding-Techniques-for-LLMs) |
Linkedin - Grounding Techniques for LLMs - AD-TEAM - 09-10-2024 ![]() 433.27 MB | 00:15:27 | mp4 | 1280X720 | 16:9 Genre:eLearning |Language:English
Files Included :
01 - Understanding grounding techniques for LLMs (2.48 MB) 02 - Setting up your LLM environment (14.48 MB) 01 - What is a hallucination (1.7 MB) 02 - Hallucination examples (1.95 MB) 03 - Comparing hallucinations across LLMs (7.93 MB) 04 - Dangers of hallucinations (6.95 MB) 05 - Challenge Finding a hallucination (893.54 KB) 06 - Solution Finding a hallucination (6.22 MB) 01 - Training LLMs on time-sensitive data (4.42 MB) 02 - Poorly curated training data (6.41 MB) 03 - Faithfulness and context (9.39 MB) 04 - Ambiguous responses (5.56 MB) 05 - Incorrect output structure (5.16 MB) 06 - Declining to respond (10.38 MB) 07 - Fine-tuning hallucinations (8.25 MB) 08 - LLM sampling techniques and adjustments (10.76 MB) 09 - Bad citations (4.28 MB) 10 - Incomplete information extraction (8.24 MB) 01 - Few-shot learning (5.06 MB) 02 - Chain of thought reasoning (7.49 MB) 03 - Structured templates (4.35 MB) 04 - Retrieval-augmented generation (6.92 MB) 05 - Updating LLM model versions (10.12 MB) 06 - Model fine-tuning for mitigating hallucinations (24.23 MB) 07 - Orchestrating workflows through model routing (18.26 MB) 08 - Challenge Automating ecommerce reviews with LLMs (3.28 MB) 09 - Solution Automating ecommerce reviews with LLMs (8.85 MB) 01 - Creating LLM evaluation pipelines (8.48 MB) 02 - LLM self-assessment pipelines (19.87 MB) 03 - Human-in-the-loop systems (15.14 MB) 04 - Specialized models for hallucination detection (24.38 MB) 05 - Building an evaluation dataset (12.84 MB) 06 - Optimizing prompts with DSPY (48.75 MB) 07 - Optimizing hallucination detections with DSPY (19.31 MB) 08 - Real-world LLM user testing (16.48 MB) 09 - Challenge A more well-rounded AI trivia agent (1.36 MB) 10 - Solution A more well-rounded AI trivia agent (8.42 MB) 01 - Ragas Evaluation paper (9.2 MB) 02 - Hallucinations in large multilingual translation models (15.26 MB) 03 - Do LLMs know what they don't know (10.33 MB) 04 - Set the Clock LLM temporal fine-tuning (8.85 MB) 05 - Review of hallucination papers (8.93 MB) 01 - Continue your practice of grounding techniques for LLMs (1.4 MB)
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