3 citations · 8 across the 16 of their papers we have counts for
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cs.CL2024★ 3 cited
FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"
Yifei Ming, Senthil Purushwalkam, Shrey Pandit +4
Ensuring faithfulness to context in large language models (LLMs) and retrieval-augmented generation (RAG) systems is crucial for reliable deployment in real-world applications, as…
cs.CL2024★ 2 cited
SFR-RAG: Towards Contextually Faithful LLMs
Xuan-Phi Nguyen, Shrey Pandit, Senthil Purushwalkam +7
Retrieval Augmented Generation (RAG), a paradigm that integrates external contextual information with large language models (LLMs) to enhance factual accuracy and relevance, has em…