Emerging synergies in causality and deep generative models: A survey
In the field of artificial intelligence (AI), the quest to understand and model data-generating
processes (DGPs) is of paramount importance. Deep generative models (DGMs) have …
processes (DGPs) is of paramount importance. Deep generative models (DGMs) have …
Cladder: Assessing causal reasoning in language models
The ability to perform causal reasoning is widely considered a core feature of intelligence. In
this work, we investigate whether large language models (LLMs) can coherently reason …
this work, we investigate whether large language models (LLMs) can coherently reason …
An interdisciplinary outlook on large language models for scientific research
In this paper, we describe the capabilities and constraints of Large Language Models
(LLMs) within disparate academic disciplines, aiming to delineate their strengths and …
(LLMs) within disparate academic disciplines, aiming to delineate their strengths and …
Diffusion language models can perform many tasks with scaling and instruction-finetuning
The recent surge of generative AI has been fueled by the generative power of diffusion
probabilistic models and the scalable capabilities of large language models. Despite their …
probabilistic models and the scalable capabilities of large language models. Despite their …
Towards causal foundation model: on duality between causal inference and attention
Foundation models have brought changes to the landscape of machine learning,
demonstrating sparks of human-level intelligence across a diverse array of tasks. However …
demonstrating sparks of human-level intelligence across a diverse array of tasks. However …
GPT-based models meet simulation: how to efficiently use large-scale pre-trained language models across simulation tasks
PJ Giabbanelli - 2023 Winter Simulation Conference (WSC), 2023 - ieeexplore.ieee.org
The disruptive technology provided by large-scale pre-trained language models (LLMs)
such as ChatGPT or GPT-4 has received significant attention in several application domains …
such as ChatGPT or GPT-4 has received significant attention in several application domains …
Applying large language models for causal structure learning in non small cell lung cancer
N Naik, A Khandelwal, M Joshi, M Atre… - 2024 IEEE 12th …, 2024 - ieeexplore.ieee.org
Causal discovery is becoming a key part in medical AI research. These methods can
enhance healthcare by identifying causal links between biomarkers, demographics …
enhance healthcare by identifying causal links between biomarkers, demographics …
Llm-enhanced causal discovery in temporal domain from interventional data
In the field of Artificial Intelligence for Information Technology Operations, causal discovery
is pivotal for operation and maintenance of graph construction, facilitating downstream …
is pivotal for operation and maintenance of graph construction, facilitating downstream …
CausalBench: A Comprehensive Benchmark for Causal Learning Capability of Large Language Models
Causality reveals fundamental principles behind data distributions in real-world scenarios,
and the capability of large language models (LLMs) to understand causality directly impacts …
and the capability of large language models (LLMs) to understand causality directly impacts …
Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework
Large language models (LLMs) can easily generate biased and discriminative responses.
As LLMs tap into consequential decision-making (eg, hiring and healthcare), it is of crucial …
As LLMs tap into consequential decision-making (eg, hiring and healthcare), it is of crucial …