18 citations · 33 across the 14 of their papers we have counts for
5 papers · 1 filter
LLM-based Corroborating and Refuting Evidence Retrieval for Scientific Claim Verification
Siyuan Wang, James R. Foulds, Md Osman Gani +1
In this paper, we introduce CIBER (Claim Investigation Based on Evidence Retrieval), an extension of the Retrieval-Augmented Generation (RAG) framework designed to identify corrobo…
Optimizing Data-driven Causal Discovery Using Knowledge-guided Search
Uzma Hasan, Md Osman Gani
Learning causal relationships solely from observational data often fails to reveal the underlying causal mechanisms due to the vast search space of possible causal graphs, which ca…
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
Uzma Hasan, Emam Hossain, Md Osman Gani
The ability to understand causality from data is one of the major milestones of human-level intelligence. Causal Discovery (CD) algorithms can identify the cause-effect relationshi…
Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference
Sahara Ali, Omar Faruque, Yiyi Huang +4
The warming of the Arctic, also known as Arctic amplification, is led by several atmospheric and oceanic drivers. However, the details of its underlying thermodynamic causes are st…
CKH: Causal Knowledge Hierarchy for Estimating Structural Causal Models from Data and Priors
Riddhiman Adib, Md Mobasshir Arshed Naved, Chih-Hao Fang +5
Structural causal models (SCMs) provide a principled approach to identifying causation from observational and experimental data in disciplines ranging from economics to medicine. H…