Javad Hosseini
Javad Hosseini is a researcher at Google Research, UK, working on natural language inference, reasoning, and problems related to factuality of large language models. Before joining Google, Javad earned his PhD at the Institute for Language, Cognition and Computation (ILCC), University of Edinburgh, under supervision of Mark Steedman. He obtained his MSc in computer science from the University of Washington while working with Hanna Hajishirzi, Oren Etzioni , and Su-In Lee. He earned his MSc and BSc (1st rank) in Computer Software Engineering from Sharif University of Technology.
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Google
Complementary Roles of Inference and Language Models in Open-domain QA
Liang Cheng
Mark Steedman
Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning (2023)
Sources of LLM Hallucination in Natural Language Inference
Nick McKenna
Tianyi Li
Liang Cheng
Mark Johnson
Mark Steedman
Findings of the Association for Computational Linguistics: EMNLP 2023
Resolving Indirect Referring Expressions for Entity Selection
Silvia Pareti
Proceedings of the Annual Meetings of the Association for Computational Linguistics (ACL 2023)
Language models are poor learners of directional inference
Tianyi Li
Sabine Weber
Mark Steedman
Findings of the Association for Computational Linguistics: EMNLP 2022, pp. 903-921
Cross-lingual Inference with A Chinese Entailment Graph
Tianyi Li
Sabine Weber
Liane Guillou
Mark Steedman
Findings of the Association for Computational Linguistics: ACL 2022, pp. 1214-1233
Open-Domain Contextual Link Prediction and its Complementarity with Entailment Graphs
Shay B. Cohen
Mark Johnson
Mark Steedman
Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 2790-2802
Multivalent Entailment Graphs for Question Answering
Nick McKenna
Liane Guillou
Sander Bijl de Vroe
Mark Johnson
Mark Steedman
Conference on Empirical Methods in Natural Language Processing (EMNLP, long papers) (2021), pp. 10758-10768
