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In this video we talk about how we can decrease the hallucinations large language models produce by using the chain-of-verification (COVE) method, presented in the paper "Chain-of-Verification (COVE) Reduces Hallucination in Large Language Models". References ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ “Chain-of-Verification (COVE) Reduces Hallucination in Large Language Models” paper: https://arxiv.org/abs/2309.11495 Related Videos ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Why Language Models Hallucinate: • Why LLMs Hallucinate Transformer Self-Attention Mechanism Explained: • Transformer Self-Attention Mechanism Visua... Jailbroken: How Does LLM Safety Training Fail? - Paper Explained: • Jailbroken: How Does LLM Safety Training F... How to Fine-tune Large Language Models Like ChatGPT with Low-Rank Adaptation (LoRA): • Low-Rank Adaptation (LoRA) Explained Multi-Head Attention (MHA), Multi-Query Attention (MQA), Grouped Query Attention (GQA) Explained: • Multi-Head Attention (MHA), Multi-Query At... LLM Prompt Engineering with Random Sampling: Temperature, Top-k, Top-p: • LLM Prompt Engineering with Random Samplin... Contents ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 00:00 - Abstract & Intro 03:43 - Related Work 06:15 - Chain-of-verification 16:35 - Experiments 22:50 - Results 24:55 - Findings 27:14 - Conclusion & Outro Follow Me ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🐦 Twitter: @datamlistic / datamlistic 📸 Instagram: @datamlistic / datamlistic 📱 TikTok: @datamlistic / datamlistic Channel Support ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ The best way to support the channel is to share the content. ;) If you'd like to also support the channel financially, donating the price of a coffee is always warmly welcomed! (completely optional and voluntary) ► Patreon: / datamlistic ► Bitcoin (BTC): 3C6Pkzyb5CjAUYrJxmpCaaNPVRgRVxxyTq ► Ethereum (ETH): 0x9Ac4eB94386C3e02b96599C05B7a8C71773c9281 ► Cardano (ADA): addr1v95rfxlslfzkvd8sr3exkh7st4qmgj4ywf5zcaxgqgdyunsj5juw5 ► Tether (USDT): 0xeC261d9b2EE4B6997a6a424067af165BAA4afE1a #llm #hallucinations #largelanguagemodels