Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation | Paper Citation Record

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Improved algorithms for linear stochastic bandits

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Alaa and Mihaela van der Schaar

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Uncertainty- based offline reinforcement learning with diversified Q-ensemble

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning

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This paper cites LLM-driven causal discovery via harmonized prior.IEEE Transactions on Knowledge and Data Engineering, 2025.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation LLM-driven causal discovery via harmonized prior.IEEE Transactions on Knowledge and Data Engineering, 2025

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Weight uncertainty in neural networks

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This paper cites Chen, Rohit Bhattacharya, and Katherine A.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Chen, Rohit Bhattacharya, and Katherine A

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This paper cites Unveiling causal reasoning in large language models: Reality or mirage? InAdvances in Neural Information Processing Systems, volume 37, 2024.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Unveiling causal reasoning in large language models: Reality or mirage? InAdvances in Neural Information Processing Systems, volume 37, 2024

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This paper cites Krishnan, and Chris J.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Krishnan, and Chris J

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This paper cites Causal discovery through synergizing large language model and data-driven reasoning.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Causal discovery through synergizing large language model and data-driven reasoning

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This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Dropout as a bayesian approximation: Representing model uncertainty in deep learning

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This paper cites Learning disentangled representations for counterfactual regression.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Learning disentangled representations for counterfactual regression

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Improving treatment effect estimation with llm-based data augmentation

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This paper cites Imbens and Donald B.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Imbens and Donald B

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This paper cites Identifying causal- effect inference failure with uncertainty-aware models.Advances in Neural Information Processing Systems, 33:11637–11649, 2020.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Identifying causal- effect inference failure with uncertainty-aware models.Advances in Neural Information Processing Systems, 33:11637–11649, 2020

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This paper cites Cladder: Assessing causal reasoning in language models.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Cladder: Assessing causal reasoning in language models

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This paper cites What uncertainties do we need in bayesian deep learning for computer vision?Advances in neural information processing systems, 30, 2017.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation What uncertainties do we need in bayesian deep learning for computer vision?Advances in neural information processing systems, 30, 2017

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Varia- tional autoencoders and nonlinear ica: A unifying framework

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This paper cites Metalearners for estimating heterogeneous treatment effects using machine learning.Proceedings of the National Academy of Sciences, 116(10):4156–4165, 2019.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Metalearners for estimating heterogeneous treatment effects using machine learning.Proceedings of the National Academy of Sciences, 116(10):4156–4165, 2019

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Causal Reasoning and Large Language Models: Opening a New Frontier for Causality

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Simple and scalable predictive uncertainty estimation using deep ensembles.Advances in neural information processing systems, 30, 2017

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Self-distilled disentangled learning for counterfactual prediction

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Large language models and causal inference in collaboration: A comprehensive survey

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Causal effect inference with deep latent-variable models

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Unresolved cited work

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This paper cites Deep Disentangled Representation Network for Treatment Effect Estimation.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Deep Disentangled Representation Network for Treatment Effect Estimation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Quasi-oracle estimation of heterogeneous treat- ment effects.Biometrika, 108(2):299–319, 2021

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation A critical look at the consistency of causal estimation with deep latent variable models

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Rosenbaum and Donald B

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Estimating individual treat- ment effect: generalization bounds and algorithms

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Adapting neural networks for the estimation of treatment effects

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Improving data-driven heterogeneous treatment effect estimation under structure uncertainty

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation DoubleLingo: Causal estimation with large language models

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation CE-RCFR: Robust counterfactual regression for consensus-enabled treatment effect estimation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Treatment effect estimation with adjustment feature selection

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Progressive generalization risk reduction for data-efficient causal effect estimation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation From supervised to generative: A novel paradigm for tabular deep learning with large language models

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Learning decomposed representations for treatment effect estimation.IEEE Transactions on Knowledge and Data Engineering, 35(5):4989– 5001, 2023

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation 𝛽-intact-VAE: Identifying and estimat- ing causal effects under limited overlap

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Neural contextual bandits with deep representation and shallow exploration

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Causal inference with conditional front-door adjustment and identifiable variational autoencoder

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Treatment effect estimation with dis- entangled latent factors.Proceedings of the AAAI Conference on Artificial Intel- ligence, 35(12):10923–10930, May 2021

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Lui, and Hang Li

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This paper cites DESCN: Deep entire space cross networks for individual treatment effect estimation.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation DESCN: Deep entire space cross networks for individual treatment effect estimation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Neural contextual bandits with UCB-based exploration

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This paper cites Causal effect estimation with mixed latent confounders and post-treatment variables.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Causal effect estimation with mixed latent confounders and post-treatment variables

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Unresolved cited work

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Unresolved cited work

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This paper cites [Goal] Compress these pre-existing confounders into a single representation.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation [Goal] Compress these pre-existing confounders into a single representation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation 12 Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Unresolved cited work

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation [Goal] Compress these heterogeneity modifiers into a single representation

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Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation [Goal] Compress these heterogeneity modifiers into a single representation

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This paper cites This suggests a certain socio-economic standing but does not provide detailed information about income, education, or employment status.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation This suggests a certain socio-economic standing but does not provide detailed information about income, education, or employment status

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This paper cites However, as a new customer, they may still be relatively sensitive to new brand strategies or product changes.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation However, as a new customer, they may still be relatively sensitive to new brand strategies or product changes

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Observation 35deceb8-a5ee-4570-a060-7522c4a430e6 · outbound

This paper cites doi: 10.1145/3534678.3539444.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation doi: 10.1145/3534678.3539444

Reference 1797

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Observation 04293d30-442b-450c-a8e3-45b993d10432 · outbound

This paper cites an unresolved cited work.

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-01T12:41:27.443235Z

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