6 papers
Enhancing Language Models for Robust Greenwashing Detection
Neil Heinrich Braun, Keane Ong, Rui Mao +2
Sustainability reports are critical for ESG assessment, yet greenwashing and vague claims often undermine their reliability. Existing NLP models lack robustness to these practices,…
Deriving Strategic Market Insights with Large Language Models: A Benchmark for Forward Counterfactual Generation
Keane Ong, Rui Mao, Deeksha Varshney +3
Counterfactual reasoning typically involves considering alternatives to actual events. While often applied to understand past events, a distinct form-forward counterfactual reasoni…
ClimaEmpact: Domain-Aligned Small Language Models and Datasets for Extreme Weather Analytics
Deeksha Varshney, Keane Ong, Rui Mao +2
Accurate assessments of extreme weather events are vital for research and policy, yet localized and granular data remain scarce in many parts of the world. This data gap limits our…
Leveraging LLMS for Top-Down Sector Allocation In Automated Trading
Ryan Quek Wei Heng, Edoardo Vittori, Keane Ong +3
This paper introduces a methodology leveraging Large Language Models (LLMs) for sector-level portfolio allocation through systematic analysis of macroeconomic conditions and market…
Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization
Keane Ong, Rui Mao, Deeksha Varshney +2
Sustainability reports are key for evaluating companies' environmental, social and governance, ESG performance, but their content is increasingly obscured by greenwashing - sustain…
ESGSenticNet: A Neurosymbolic Knowledge Base for Corporate Sustainability Analysis
Keane Ong, Rui Mao, Deeksha Varshney +5
Evaluating corporate sustainability performance is essential to drive sustainable business practices, amid the need for a more sustainable economy. However, this is hindered by the…