multi-document-rag-with-RAGAS / evaluation /sample_questions.json
dharandhamo's picture
Add Multi-Document RAG project with Nvidia integration
f813ba1
Raw
History Blame Contribute Delete
5.82 kB
[
{
"id": "q001",
"type": "factual",
"question": "What dataset was used in this study?",
"ground_truth": "The specific dataset used depends on the paper being queried. Common datasets include ImageNet, COCO, SQuAD, and GLUE benchmark.",
"doc_hint": null
},
{
"id": "q002",
"type": "factual",
"question": "What is the primary evaluation metric reported in the paper?",
"ground_truth": "The primary evaluation metric varies by paper but commonly includes accuracy, F1-score, BLEU score, or ROUGE score.",
"doc_hint": null
},
{
"id": "q003",
"type": "factual",
"question": "Who are the authors of this research paper?",
"ground_truth": "The authors are listed in the paper's header section and vary by document.",
"doc_hint": null
},
{
"id": "q004",
"type": "factual",
"question": "What baseline models were compared against in the experiments?",
"ground_truth": "Baseline models typically include state-of-the-art methods from prior work in the same domain.",
"doc_hint": null
},
{
"id": "q005",
"type": "comparative",
"question": "How does the proposed method differ from the baseline approach in terms of architecture?",
"ground_truth": "The proposed method typically introduces novel architectural components or modifications to existing architectures that differentiate it from baselines.",
"doc_hint": null
},
{
"id": "q006",
"type": "comparative",
"question": "Compare the computational efficiency of the methods described in these papers.",
"ground_truth": "Computational efficiency varies based on model size, training time, inference speed, and hardware requirements.",
"doc_hint": null
},
{
"id": "q007",
"type": "comparative",
"question": "What are the similarities and differences in the training procedures used across these studies?",
"ground_truth": "Training procedures may share common elements like optimizer choice but differ in learning rates, batch sizes, and data augmentation strategies.",
"doc_hint": null
},
{
"id": "q008",
"type": "comparative",
"question": "How do the experimental results in paper A contrast with those in paper B?",
"ground_truth": "Results may show different performance levels on the same benchmarks due to methodological differences.",
"doc_hint": null
},
{
"id": "q009",
"type": "summarization",
"question": "Summarize the key findings of this paper.",
"ground_truth": "Key findings typically include the main contributions, performance improvements, and novel insights presented in the paper.",
"doc_hint": null
},
{
"id": "q010",
"type": "summarization",
"question": "Provide a brief overview of the methodology section.",
"ground_truth": "The methodology section describes the proposed approach, model architecture, training procedure, and evaluation protocol.",
"doc_hint": null
},
{
"id": "q011",
"type": "summarization",
"question": "What are the main contributions claimed by the authors?",
"ground_truth": "Main contributions typically include novel methods, improved performance, new datasets, or theoretical insights.",
"doc_hint": null
},
{
"id": "q012",
"type": "summarization",
"question": "Summarize the related work section and identify the research gap addressed.",
"ground_truth": "The related work section reviews prior approaches and identifies limitations that the current paper aims to address.",
"doc_hint": null
},
{
"id": "q013",
"type": "multi_hop",
"question": "What evidence supports the main claim in section 3, and how does it connect to the conclusions?",
"ground_truth": "Evidence in section 3 typically includes experimental results, ablation studies, or theoretical proofs that support the paper's main thesis.",
"doc_hint": null
},
{
"id": "q014",
"type": "multi_hop",
"question": "Based on the limitations discussed, what future research directions could address the identified gaps?",
"ground_truth": "Future directions may include scaling the approach, applying it to new domains, or addressing computational constraints.",
"doc_hint": null
},
{
"id": "q015",
"type": "multi_hop",
"question": "How do the theoretical assumptions in the paper relate to the empirical results observed?",
"ground_truth": "Theoretical assumptions should be validated by empirical results, though gaps may exist between theory and practice.",
"doc_hint": null
},
{
"id": "q016",
"type": "multi_hop",
"question": "If the dataset size were doubled, what impact would you expect on the reported metrics based on the paper's analysis?",
"ground_truth": "Based on scaling analyses, doubling the dataset typically leads to improved performance with diminishing returns.",
"doc_hint": null
},
{
"id": "q017",
"type": "out_of_scope",
"question": "What is the current stock price of NVIDIA?",
"ground_truth": "This information is not available in the provided documents.",
"doc_hint": null
},
{
"id": "q018",
"type": "out_of_scope",
"question": "What will the weather be like in New York tomorrow?",
"ground_truth": "This information is not available in the provided documents.",
"doc_hint": null
},
{
"id": "q019",
"type": "out_of_scope",
"question": "Who won the FIFA World Cup in 2022?",
"ground_truth": "This information is not available in the provided documents.",
"doc_hint": null
},
{
"id": "q020",
"type": "out_of_scope",
"question": "How do I cook a perfect risotto?",
"ground_truth": "This information is not available in the provided documents.",
"doc_hint": null
}
]