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 multi-agent interactions.

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