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Found 9 papers, 2 papers with code
Proverbs Run in Pairs: Evaluating Proverb Translation Capability of Large Language Model
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.
Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs
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.
Modelling Political Coalition Negotiations Using LLM-based Agents
Coalition negotiations are a cornerstone of parliamentary democracies, characterised by complex interactions and strategic communications among political parties.
NormMark: A Weakly Supervised Markov Model for Socio-cultural Norm Discovery
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
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.
Neural-Symbolic Commonsense Reasoner with Relation Predictors
The dynamic nature of commonsense knowledge postulates models capable of performing multi-hop reasoning over new situations.
Domain Adaptative Causality Encoder
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
Causal relationships form the basis for reasoning and decision-making in Artificial Intelligence systems.
COSMO: Conditional SEQ2SEQ-based Mixture Model for Zero-Shot Commonsense Question Answering
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.
