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Nov 25, 2024
Can small errors disrupt RAG pipelines?
Can minor document typos disrupt RAG systems? Explore how small errors impact retriever and reader components and overall AI accuracy.
Cobus Greyling
Cobus Greyling
Nov 21, 2024
Data design for fine-tuning to improve small language model behaviour
Learn how to improve Small Language Model behavior through data design, using techniques like Prompt Erasure and Partial Answer Masking for better reasoning.
Cobus Greyling
Cobus Greyling
Nov 21, 2024
Improve conversational UIs using social intelligence
Learn how social intelligence improves conversational UIs by making AI interactions more natural, empathetic, and context-aware.
Cobus Greyling
Cobus Greyling
Nov 18, 2024
Agentic Search-Augmented Factuality Evaluator (SAFE) for LLMs
Agentic Search-Augmented Factuality Evaluator (SAFE) For LLMs This study demonstrates that an LLM agent can outperform crowdsourced human annotators…
Cobus Greyling
Cobus Greyling
Nov 15, 2024
FaaF: Facts as a function for evaluating RAG
There has been instances where another Language Model is used to vet the RAG output, which fails to detect incorrect and incomplete generated data.
Cobus Greyling
Cobus Greyling
Nov 14, 2024
Disambiguation: Dynamic context for effective RAG question suggestions
Learn how dynamic context and disambiguation improve RAG question suggestions, boosting relevance, accuracy, and user experience in AI search.
Cobus Greyling
Cobus Greyling
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