Search Results for author: Farhad Moghimifar

Found 9 papers, 2 papers with code

Proverbs Run in Pairs: Evaluating Proverb Translation Capability of Large Language Model

no code implementations21 Jan 2025 Minghan Wang, Viet-Thanh Pham, Farhad Moghimifar, Thuy-Trang Vu

Despite achieving remarkable performance, machine translation (MT) research remains underexplored in terms of translating cultural elements in languages, such as idioms, proverbs, and colloquial expressions.

Language Modeling Language Modelling +4

Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs

no code implementations3 Jun 2024 Fatemeh Shiri, Van Nguyen, Farhad Moghimifar, John Yoo, Gholamreza Haffari, Yuan-Fang Li

Large Language Models (LLMs) demonstrate significant capabilities in processing natural language data, promising efficient knowledge extraction from diverse textual sources to enhance situational awareness and support decision-making.

Decision Making Event Argument Extraction +4

Modelling Political Coalition Negotiations Using LLM-based Agents

no code implementations18 Feb 2024 Farhad Moghimifar, Yuan-Fang Li, Robert Thomson, Gholamreza Haffari

Coalition negotiations are a cornerstone of parliamentary democracies, characterised by complex interactions and strategic communications among political parties.

Language Modeling Language Modelling +1

NormMark: A Weakly Supervised Markov Model for Socio-cultural Norm Discovery

no code implementations26 May 2023 Farhad Moghimifar, Shilin Qu, Tongtong Wu, Yuan-Fang Li, Gholamreza Haffari

Norms, which are culturally accepted guidelines for behaviours, can be integrated into conversational models to generate utterances that are appropriate for the socio-cultural context.

Few-shot Domain-Adaptive Visually-fused Event Detection from Text

no code implementations4 May 2023 Farhad Moghimifar, Fatemeh Shiri, Van Nguyen, Reza Haffari, Yuan-Fang Li

In this paper, we present a novel domain-adaptive visually-fused event detection approach that can be trained on a few labelled image-text paired data points.

Event Detection

Domain Adaptative Causality Encoder

1 code implementation ALTA 2020 Farhad Moghimifar, Gholamreza Haffari, Mahsa Baktashmotlagh

Our experiments on four different benchmark causality datasets demonstrate the superiority of our approach over the existing baselines, by up to 7% improvement, on the tasks of identification and localisation of the causal relations from the text.

Learning Causal Bayesian Networks from Text

no code implementations ALTA 2020 Farhad Moghimifar, Afshin Rahimi, Mahsa Baktashmotlagh, Xue Li

Causal relationships form the basis for reasoning and decision-making in Artificial Intelligence systems.

Decision Making Form

COSMO: Conditional SEQ2SEQ-based Mixture Model for Zero-Shot Commonsense Question Answering

1 code implementation COLING 2020 Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Mahsa Baktashmotlagh, Gholamreza Haffari

However, current approaches in this realm lack the ability to perform commonsense reasoning upon facing an unseen situation, mostly due to incapability of identifying a diverse range of implicit social relations.

Question Answering

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