google-research-datasets/Attributed-QA
We believe the ability of an LLM to attribute the text that it generates is likely to be crucial for both system developers and users in information-seeking scenarios. This release consists of human-rated system outputs for a new question-answering task, Attributed Question Answering (AQA).
PythonApache-2.0
Stargazers
- aashiqmuhamedCarnegie Mellon University
- ArturHDHeidelberg University
- calebmcclainAnunaAI
- CodingLLShanghai Jiaotong University
- devanshkhandekarIndia
- devinschumacher@serp-ai
- djwei96The University of Hong Kong
- fixback21
- francislabountyjr
- fRedelaarAmsterdam
- Gouzi3618
- gsartiUniversity of Groningen
- hanane-djeddalParis
- hbad71877
- hkf
- iniuxy
- Juanting-XuShanghai JiaoTong University
- jxzhangjhuIntuit AI Research
- mikfulUniversity of Bath
- neuroninterpretation
- northenpulsar
- rachelruijiayangNew York, NY
- raonigabrielCuritiba - Paraná, Brazil
- riyazbhatIBM
- samos123@GoogleCloudPlatform
- SaneshNarayanan
- shashankprBangalore
- SS-YuJJ
- terrettaNYC
- wonhyeongseoAutomationAnywhere (contract)
- WVGGIT
- yaqingwangGoogle Deepmind
- yunfan42Shanghai
- yv
- zjpbinary
- ZubinGouTsinghua University