Short-text Multi-doc Question Answering on RGB noise robustness testbed (test) benchmark leaderboard · SOTA2 Research

Short-text Multi-doc Question Answering on RGB noise robustness testbed (test)

96EM (Noise 0)Our model (PAM QA)

Evaluation Results

Method	Links
Our model (PAM QA)2023.11		96	90.67	90	85.5	67.33
GPT3.5-Turbo2023.11		95.67	94.67	91	87.67	70.67
Qwen-14B-Chat2023.11		94.67	92	88	85.3	69.67
Baichuan2-13B-Chat2023.11		93	90.33	89	82.33	63.33
ChatGLM3-6B2023.11		91.67	90	89	84.67	66.33
ChatGLM2-6B2023.11		86.67	82.33	76.67	72.33	54