seven QA datasets

The 'seven QA datasets' is a benchmark that contains various question-answering datasets used to evaluate the performance of large language models in responding to questions and their susceptibility to peer influence during answer revision.

Papers using seven QA datasets (3)

Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement2026Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity2026Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning2026