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[ FreeCourseWeb com ] Linkedin - Grounding Techniques for LLMs
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01 - Introduction
01 - Understanding grounding techniques for LLMs.mp4
01 - Understanding grounding techniques for LLMs.srt
02 - Setting up your LLM environment.mp4
02 - Setting up your LLM environment.srt
02 - 1. Basic LLM Hallucinations
01 - What is a hallucination.mp4
01 - What is a hallucination.srt
02 - Hallucination examples.mp4
02 - Hallucination examples.srt
03 - Comparing hallucinations across LLMs.mp4
03 - Comparing hallucinations across LLMs.srt
04 - Dangers of hallucinations.mp4
04 - Dangers of hallucinations.srt
05 - Challenge Finding a hallucination.mp4
05 - Challenge Finding a hallucination.srt
06 - Solution Finding a hallucination.mp4
06 - Solution Finding a hallucination.srt
03 - 2. Types of Hallucinations
01 - Training LLMs on time-sensitive data.mp4
01 - Training LLMs on time-sensitive data.srt
02 - Poorly curated training data.mp4
02 - Poorly curated training data.srt
03 - Faithfulness and context.mp4
03 - Faithfulness and context.srt
04 - Ambiguous responses.mp4
04 - Ambiguous responses.srt
05 - Incorrect output structure.mp4
05 - Incorrect output structure.srt
06 - Declining to respond.mp4
06 - Declining to respond.srt
07 - Fine-tuning hallucinations.mp4
07 - Fine-tuning hallucinations.srt
08 - LLM sampling techniques and adjustments.mp4
08 - LLM sampling techniques and adjustments.srt
09 - Bad citations.mp4
09 - Bad citations.srt
10 - Incomplete information extraction.mp4
10 - Incomplete information extraction.srt
04 - 3. Mitigating Hallucinations
01 - Few-shot learning.mp4
01 - Few-shot learning.srt
02 - Chain of thought reasoning.mp4
02 - Chain of thought reasoning.srt
03 - Structured templates.mp4
03 - Structured templates.srt
04 - Retrieval-augmented generation.mp4
04 - Retrieval-augmented generation.srt
05 - Updating LLM model versions.mp4
05 - Updating LLM model versions.srt
06 - Model fine-tuning for mitigating hallucinations.mp4
06 - Model fine-tuning for mitigating hallucinations.srt
07 - Orchestrating workflows through model routing.mp4
07 - Orchestrating workflows through model routing.srt
08 - Challenge Automating ecommerce reviews with LLMs.mp4
08 - Challenge Automating ecommerce reviews with LLMs.srt
09 - Solution Automating ecommerce reviews with LLMs.mp4
09 - Solution Automating ecommerce reviews with LLMs.srt
05 - 4. Detecting Hallucinations
01 - Creating LLM evaluation pipelines.mp4
01 - Creating LLM evaluation pipelines.srt
02 - LLM self-assessment pipelines.mp4
02 - LLM self-assessment pipelines.srt
03 - Human-in-the-loop systems.mp4
03 - Human-in-the-loop systems.srt
04 - Specialized models for hallucination detection.mp4
04 - Specialized models for hallucination detection.srt
05 - Building an evaluation dataset.mp4
05 - Building an evaluation dataset.srt
06 - Optimizing prompts with DSPY.mp4
06 - Optimizing prompts with DSPY.srt
07 - Optimizing hallucination detections with DSPY.mp4
07 - Optimizing hallucination detections with DSPY.srt
08 - Real-world LLM user testing.mp4
08 - Real-world LLM user testing.srt
09 - Challenge A more well-rounded AI trivia agent.mp4
09 - Challenge A more well-rounded AI trivia agent.srt
10 - Solution A more well-rounded AI trivia agent.mp4
10 - Solution A more well-rounded AI trivia agent.srt
06 - 5. Hallucination Paper Review
01 - Ragas Evaluation paper.mp4
01 - Ragas Evaluation paper.srt
02 - Hallucinations in large multilingual translation models.mp4
02 - Hallucinations in large multilingual translation models.srt
03 - Do LLMs know what they don’t know.mp4
03 - Do LLMs know what they don’t know.srt
04 - Set the Clock LLM temporal fine-tuning.mp4
04 - Set the Clock LLM temporal fine-tuning.srt
05 - Review of hallucination papers.mp4
05 - Review of hallucination papers.srt
07 - Conclusion
01 - Continue your practice of grounding techniques for LLMs.mp4
01 - Continue your practice of grounding techniques for LLMs.srt
Bonus Resources.txt
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