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Survey on factuality in large language models: Knowledge, retrieval and domain-specificity
This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As
LLMs find applications across diverse domains, the reliability and accuracy of their outputs …
LLMs find applications across diverse domains, the reliability and accuracy of their outputs …
Knowledge editing for large language models: A survey
Large Language Models (LLMs) have recently transformed both the academic and industrial
landscapes due to their remarkable capacity to understand, analyze, and generate texts …
landscapes due to their remarkable capacity to understand, analyze, and generate texts …
[PDF][PDF] Retrieval-augmented generation for large language models: A survey
Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …
challenges in practical applications, such as hallucinations, slow knowledge updates, and …
Mass-editing memory in a transformer
Recent work has shown exciting promise in updating large language models with new
memories, so as to replace obsolete information or add specialized knowledge. However …
memories, so as to replace obsolete information or add specialized knowledge. However …
Editing large language models: Problems, methods, and opportunities
Despite the ability to train capable LLMs, the methodology for maintaining their relevancy
and rectifying errors remains elusive. To this end, the past few years have witnessed a surge …
and rectifying errors remains elusive. To this end, the past few years have witnessed a surge …
One embedder, any task: Instruction-finetuned text embeddings
We introduce INSTRUCTOR, a new method for computing text embeddings given task
instructions: every text input is embedded together with instructions explaining the use case …
instructions: every text input is embedded together with instructions explaining the use case …
Atlas: Few-shot learning with retrieval augmented language models
Large language models have shown impressive few-shot results on a wide range of tasks.
However, when knowledge is key for such results, as is the case for tasks such as question …
However, when knowledge is key for such results, as is the case for tasks such as question …
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …
capabilities with increasing scale. Despite their potentially transformative impact, these new …
Prompting gpt-3 to be reliable
Large language models (LLMs) show impressive abilities via few-shot prompting.
Commercialized APIs such as OpenAI GPT-3 further increase their use in real-world …
Commercialized APIs such as OpenAI GPT-3 further increase their use in real-world …
Memory-based model editing at scale
Even the largest neural networks make errors, and once-correct predictions can become
invalid as the world changes. Model editors make local updates to the behavior of base (pre …
invalid as the world changes. Model editors make local updates to the behavior of base (pre …