no code implementations • 10 Dec 2024 • Tianyi Li, Erenay Dayanik, Shubhi Tyagi, Andrea Pierleoni
In this paper, we present HalluCana, a canary lookahead to detect and correct factuality hallucinations of Large Language Models (LLMs) in long-form generation.
1 code implementation • 19 Apr 2024 • Nacime Bouziani, Shubhi Tyagi, Joseph Fisher, Jens Lehmann, Andrea Pierleoni
Extracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE).
Ranked #1 on
Coreference Resolution
on DWIE
3 code implementations • NAACL (ACL) 2022 • Tom Ayoola, Shubhi Tyagi, Joseph Fisher, Christos Christodoulopoulos, Andrea Pierleoni
The model is capable of generalising to large-scale knowledge bases such as Wikidata (which has 15 times more entities than Wikipedia) and of zero-shot entity linking.
Ranked #1 on
Entity Linking
on WebQSP-WD
(using extra training data)
1 code implementation • NAACL 2021 • Shubhi Tyagi, Antonio Bonafonte, Jaime Lorenzo-Trueba, Javier Latorre
Developing Text Normalization (TN) systems for Text-to-Speech (TTS) on new languages is hard.
no code implementations • 2 Dec 2019 • Shubhi Tyagi, Marco Nicolis, Jonas Rohnke, Thomas Drugman, Jaime Lorenzo-Trueba
Recent advances in Text-to-Speech (TTS) have improved quality and naturalness to near-human capabilities when considering isolated sentences.