Posts tagged Hallucinations
Best LLMs for RAG: Top Open And Closed Source Models
Top Open And Closed Source LLMs For Short, Medium and Long Context RAG
Survey of Hallucinations in Multimodal Models
An exploration of type of hallucinations in multimodal models and ways to mitigate them.
Mastering RAG: 4 Metrics to Improve Performance
Unlock the potential of RAG analysis with 4 essential metrics to enhance performance and decision-making. Learn how to master RAG methodology for greater effectiveness in project management and strategic planning.
5 Techniques for Detecting LLM Hallucinations
A survey of hallucination detection techniques
Galileo Luna: Advancing LLM Evaluation Beyond GPT-3.5
Research backed evaluation foundation models for enterprise scale
RAG LLM Prompting Techniques to Reduce Hallucinations
Dive into our blog for advanced strategies like ThoT, CoN, and CoVe to minimize hallucinations in RAG applications. Explore emotional prompts and ExpertPrompting to enhance LLM performance. Stay ahead in the dynamic RAG landscape with reliable insights for precise language models. Read now for a deep dive into refining LLMs.
Mastering RAG: 8 Scenarios To Evaluate Before Going To Production
Learn how to Master RAG. Delve deep into 8 scenarios that are essential for testing before going to production.
A Metrics-First Approach to LLM Evaluation
Learn about different types of LLM evaluation metrics needed for generative applications
Webinar: Mitigating LLM Hallucinations with Deeplearning.ai
Join in on this workshop where we will showcase some powerful metrics to evaluate the quality of the inputs (data quality, RAG context quality, etc) and outputs (hallucinations) with a focus on both RAG and fine-tuning use cases.
5 Key Takeaways from Biden's AI Executive Order
Explore the transformative impact of President Biden's Executive Order on AI, focusing on safety, privacy, and innovation. Discover key takeaways, including the need for robust Red-teaming processes, transparent safety test sharing, and privacy-preserving techniques.
Fixing RAG System Hallucinations with Pinecone & Galileo
Watch our webinar with Pinecone on optimizing RAG & chain-based GenAI! Learn strategies to combat hallucinations, leverage vector databases, and enhance RAG analytics for efficient debugging.
Webinar: Announcing Galileo LLM Studio
Webinar - Announcing Galileo LLM Studio: A Smarter Way to Build LLM Applications
Optimizing LLM Performance: RAG vs. Fine-Tuning
A comprehensive guide to retrieval-augmented generation (RAG), fine-tuning, and their combined strategies in Large Language Models (LLMs).
Introducing the Hallucination Index
The Hallucination Index provides a comprehensive evaluation of 11 leading LLMs' propensity to hallucinate during common generative AI tasks.
Introducing ChainPoll: Enhancing LLM Evaluation
ChainPoll: A High Efficacy Method for LLM Hallucination Detection. ChainPoll leverages Chaining and Polling or Ensembling to help teams better detect LLM hallucinations. Read more at rungalileo.io/blog/chainpoll.
Mastering RAG: Advanced Chunking Techniques for LLM Applications
Learn advanced chunking techniques tailored for Language Model (LLM) applications with our guide on Mastering RAG. Elevate your projects by mastering efficient chunking methods to enhance information processing and generation capabilities.
Understanding LLM Hallucinations Across Generative Tasks
The creation of human-like text with Natural Language Generation (NLG) has improved recently because of advancements in Transformer-based language models. This has made the text produced by NLG helpful for creating summaries, generating dialogue, or transforming data into text. However, there is a problem: these deep learning systems sometimes make up or "hallucinate" text that was not intended, which can lead to worse performance and disappoint users in real-world situations.
LLM Hallucination Index: RAG Special
The LLM Hallucination Index ranks 22 of the leading models based on their performance in real-world scenarios. We hope this index helps AI builders make informed decisions about which LLM is best suited for their particular use case and need.
A Framework to Detect & Reduce LLM Hallucinations
Learn about how to identify and detect LLM hallucinations
Webinar – Galileo Protect: Real-Time Hallucination Firewall
We’re excited to announce Galileo Protect – an advanced GenAI firewall that intercepts hallucinations, prompt attacks, security threats, and more in real-time! Register for our upcoming webinar to see Protect live in action.
Introducing Protect: Real-Time Hallucination Firewall
We're thrilled to unveil Galileo Protect, an advanced GenAI firewall solution that intercepts hallucinations, prompt attacks, security threats, and more in real-time.
Mastering RAG: Adaptive & Corrective Self RAFT
A technique to reduce hallucinations drastically in RAG with self reflection and finetuning