Thema5026: Unterschied zwischen den Versionen

Version vom 5. April 2023, 11:31 Uhr

Multi-hop Retrieval and Reasoning with Language Models for Fake News Detection

Informationen zur Arbeit

Abschlussarbeitstyp: Master
Betreuer: Jin Liu, Prof. Dr. York Sure-Vetter
Forschungsgruppe: Web Science
Partner: FZI Forschungszentrum Informatik
Archivierungsnummer: 5026
Abschlussarbeitsstatus: Offen
Beginn: 11. April 2023
Abgabe: unbekannt

Weitere Informationen

The spread of fake news has caused more and more concern in the public. Reliable information retrieval is essential for fact-checking. Multi-hop information retrieval requires the extraction of information from several sources. The reasoning step processes the retrieved information and verifies the corresponding claim. In this thesis, we focus on the HOVER dataset with pre-trained large language models. Feel free to contact us (jin liu∂fzi de)

Ausschreibung: Download (pdf)

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 |Beginn=2023/04/11
 |Ausschreibung=Multihop-Retrieval_Reasoning.pdf
-|Beschreibung DE=The spread of fake news has caused more and more concern in the public. Reliable information retrieval is essential for fact-checking. Multi-hop information retrieval requires the extraction of information from several sources. The reasoning step processes the retrieved information and verifies the corresponding claim. In this thesis, we focus on the HOVER dataset with pre-trained large language models.
+|Beschreibung DE=The spread of fake news has caused more and more concern in the public. Reliable information retrieval is essential for fact-checking. Multi-hop information retrieval requires the extraction of information from several sources. The reasoning step processes the retrieved information and verifies the corresponding claim. In this thesis, we focus on the HOVER dataset with pre-trained large language models. Feel free to contact us (jin.liu@fzi.de)
 }}