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Handling Causal Tasks by Large Language Models: From Discovery to Reasoning

https://doi.org/10.2139/ssrn.5222342
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inferredcites →https://doi.org/10.1002/jae.2386openalex-snapshot
Doubly Robust Estimation of Causal Effects with Multivalued Treatments: An Application to the Returns to Schooling
inferredcites →https://doi.org/10.1002/widm.1449openalex-snapshot
Methods and tools for causal discovery and causal inference
inferredcites →https://doi.org/10.1007/978-981-96-0573-6_12openalex-snapshot
Deconfounded Causality-Aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
inferredcites →https://doi.org/10.1007/s10654-020-00703-7openalex-snapshot
Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking
inferredcites →https://doi.org/10.1007/s40471-022-00288-7openalex-snapshot
Causal Inference Challenges and New Directions for Epidemiologic Research on the Health Effects of Social Policies
inferredcites →https://doi.org/10.1016/j.cedpsych.2020.101861openalex-snapshot
An attributional theory of motivation
inferredcites →https://doi.org/10.1016/j.indmarman.2019.12.008openalex-snapshot
Effectual and causal reasoning in the adoption of marketing automation
inferredcites →https://doi.org/10.1037/1528-3542.3.3.254openalex-snapshot
The appraisal basis of anger: Specificity, necessity and sufficiency of components.
inferredcites →https://doi.org/10.1037/met0000226openalex-snapshot
Estimating causal effects in linear regression models with observational data: The instrumental variables regression model.
inferredcites →https://doi.org/10.1038/s41467-020-17419-7openalex-snapshot
Improving the accuracy of medical diagnosis with causal machine learning
inferredcites →https://doi.org/10.1038/s41467-020-20516-2openalex-snapshot
Graphical analysis for phenome-wide causal discovery in genotyped population-scale biobanks
inferredcites →https://doi.org/10.1080/00949655.2018.1505197openalex-snapshot
Elements of causal inference: foundations and learning algorithms
inferredcites →https://doi.org/10.1080/01621459.1996.10476902openalex-snapshot
Identification of Causal Effects Using Instrumental Variables
inferredcites →https://doi.org/10.1093/aje/kwaa172openalex-snapshot
Identification and Estimation of Causal Effects Using a Negative-Control Exposure in Time-Series Studies With Applications to Environmental Epidemiology
inferredcites →https://doi.org/10.1109/icsme58846.2023.00040openalex-snapshot
Benchmarking Causal Study to Interpret Large Language Models for Source Code
inferredcites →https://doi.org/10.1109/itsc57777.2023.10422308openalex-snapshot
Domain Knowledge Distillation from Large Language Model: An Empirical Study in the Autonomous Driving Domain
inferredcites →https://doi.org/10.1109/tai.2026.3703427openalex-snapshot
CausalBN-Bench: A Comprehensive Benchmark for Causal Learning Capability of LLMs
inferredcites →https://doi.org/10.1109/tpami.2021.3121705openalex-snapshot
Deconfounded Image Captioning: A Causal Retrospect
inferredcites →https://doi.org/10.1109/tpami.2023.3284038openalex-snapshot
Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering
inferredcites →https://doi.org/10.1111/1471-0528.15199openalex-snapshot
Randomised controlled trials – the gold standard for effectiveness research
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Detecting and quantifying causal associations in large nonlinear time series datasets
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AI model GPT-3 (dis)informs us better than humans
inferredcites →https://doi.org/10.1145/3397269openalex-snapshot
A Survey of Learning Causality with Data
inferredcites →https://doi.org/10.1145/3444944openalex-snapshot
A Survey on Causal Inference
inferredcites →https://doi.org/10.1145/3501714.3501743openalex-snapshot
On Pearl’s Hierarchy and the Foundations of Causal Inference
inferredcites →https://doi.org/10.1145/3673791.3698411openalex-snapshot
Optimizing LLMs with Direct Preferences: A Data Efficiency Perspective
inferredcites →https://doi.org/10.1145/3699518openalex-snapshot
Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application
inferredcites →https://doi.org/10.1146/annurev-publhealth-031811-124606openalex-snapshot
Causal Inference in Public Health
inferredcites →https://doi.org/10.1162/tacl_a_00065openalex-snapshot
Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
inferredcites →https://doi.org/10.1162/tacl_a_00101openalex-snapshot
Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations
inferredcites →https://doi.org/10.1186/s40535-016-0018-xopenalex-snapshot
Causal discovery and inference: concepts and recent methodological advances
inferredcites →https://doi.org/10.1257/jel.20191597openalex-snapshot
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
inferredcites →https://doi.org/10.1561/104.00000036openalex-snapshot
Shock-Based Causal Inference in Corporate Finance and Accounting Research
inferredcites →https://doi.org/10.1609/aaai.v31i1.10958openalex-snapshot
SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents
inferredcites →https://doi.org/10.1609/aaai.v35i15.17630openalex-snapshot
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation
inferredcites →https://doi.org/10.1609/aaai.v38i10.29047openalex-snapshot
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction
inferredcites →https://doi.org/10.1609/aaaiss.v4i1.31764openalex-snapshot
Cause and Effect: Can Large Language Models Truly Understand Causality?
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.703openalex-snapshot
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-demos.6openalex-snapshot
Transformers: State-of-the-Art Natural Language Processing
inferredcites →https://doi.org/10.18653/v1/2022.emnlp-main.60openalex-snapshot
MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction
inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.940openalex-snapshot
CRAB: Assessing the Strength of Causal Relationships Between Real-world Events
inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.574openalex-snapshot
The Magic of IF: Investigating Causal Reasoning Abilities in Large Language Models of Code
inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.824openalex-snapshot
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
inferredcites →https://doi.org/10.18653/v1/2023.findings-emnlp.743openalex-snapshot
Is ChatGPT a Good Causal Reasoner? A Comprehensive Evaluation
inferredcites →https://doi.org/10.18653/v1/2023.wassa-1.33openalex-snapshot
Can ChatGPT Understand Causal Language in Science Claims?
inferredcites →https://doi.org/10.18653/v1/2024.emnlp-main.381openalex-snapshot
Can Large Language Models Learn Independent Causal Mechanisms?
inferredcites →https://doi.org/10.18653/v1/2024.findings-acl.548openalex-snapshot
Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data
inferredcites →https://doi.org/10.18653/v1/2024.findings-acl.843openalex-snapshot
Looking Right is Sometimes Right: Investigating the Capabilities of Decoder-only LLMs for Sequence Labeling
inferredcites →https://doi.org/10.18653/v1/2025.findings-naacl.317openalex-snapshot
Neuro-Symbolic Integration Brings Causal and Reliable Reasoning Proofs
inferredcites →https://doi.org/10.18653/v1/2025.findings-naacl.327openalex-snapshot
Causal Inference with Large Language Model: A Survey
inferredcites →https://doi.org/10.18653/v1/n18-1202openalex-snapshot
Deep Contextualized Word Representations
inferredcites →https://doi.org/10.18653/v1/n19-1179openalex-snapshot
Modeling Document-level Causal Structures for Event Causal Relation Identification
inferredcites →https://doi.org/10.18653/v1/w17-2711openalex-snapshot
The Event StoryLine Corpus: A New Benchmark for Causal and Temporal Relation Extraction
inferredcites →https://doi.org/10.2307/2291629openalex-snapshot
Identification of Causal Effects Using Instrumental Variables
inferredcites →https://doi.org/10.24963/ijcai.2020/502openalex-snapshot
Guided Generation of Cause and Effect
inferredcites →https://doi.org/10.3115/v1/w14-0702openalex-snapshot
Annotating Causality in the TempEval-3 Corpus
inferredcites →https://doi.org/10.3386/w26104openalex-snapshot
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-snapshot
AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale
inferredcites →https://doi.org/10.4230/lipics.giscience.2023.43openalex-snapshot
Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.4230/oasics.slate.2022.19openalex-snapshot
Analysing Off-The-Shelf Options for Question Answering with Portuguese FAQs
inferredcites →https://doi.org/10.48550/arxiv.1409.3215openalex-snapshot
Sequence to Sequence Learning with Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1812.10757openalex-snapshot
Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
inferredcites →https://doi.org/10.48550/arxiv.1906.01732openalex-snapshot
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
inferredcites →https://doi.org/10.48550/arxiv.2105.14553openalex-snapshot
Defending Pre-trained Language Models from Adversarial Word Substitutions Without Performance Sacrifice
inferredcites →https://doi.org/10.48550/arxiv.2107.01126openalex-snapshot
Interactive Causal Structure Discovery in Earth System Sciences
inferredcites →https://doi.org/10.48550/arxiv.2206.10591openalex-snapshot
Can Foundation Models Talk Causality?
inferredcites →https://doi.org/10.48550/arxiv.2209.14279openalex-snapshot
Causal Proxy Models for Concept-Based Model Explanations
inferredcites →https://doi.org/10.48550/arxiv.2301.13819openalex-snapshot
Causal-Discovery Performance of ChatGPT in the context of Neuropathic Pain Diagnosis
inferredcites →https://doi.org/10.48550/arxiv.2303.05279openalex-snapshot
Can large language models build causal graphs?
inferredcites →https://doi.org/10.48550/arxiv.2303.13375openalex-snapshot
Capabilities of GPT-4 on Medical Challenge Problems
inferredcites →https://doi.org/10.48550/arxiv.2304.03277openalex-snapshot
Instruction Tuning with GPT-4
inferredcites →https://doi.org/10.48550/arxiv.2304.05524openalex-snapshot
Understanding Causality with Large Language Models: Feasibility and Opportunities
inferredcites →https://doi.org/10.48550/arxiv.2305.00050openalex-snapshot
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
inferredcites →https://doi.org/10.48550/arxiv.2306.05836openalex-snapshot
Can Large Language Models Infer Causation from Correlation?
inferredcites →https://doi.org/10.48550/arxiv.2308.13067openalex-snapshot
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal
inferredcites →https://doi.org/10.48550/arxiv.2309.13701openalex-snapshot
ALLURE: Auditing and Improving LLM-based Evaluation of Text using Iterative In-Context-Learning
inferredcites →https://doi.org/10.48550/arxiv.2310.00603openalex-snapshot
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
inferredcites →https://doi.org/10.48550/arxiv.2310.05863openalex-snapshot
Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models
inferredcites →https://doi.org/10.48550/arxiv.2310.05914openalex-snapshot
NEFTune: Noisy Embeddings Improve Instruction Finetuning
inferredcites →https://doi.org/10.48550/arxiv.2310.15117openalex-snapshot
CAUSAL ORDER: THE KEY TO LEVERAGING IMPERFECT EXPERTS IN CAUSAL INFERENCE
inferredcites →https://doi.org/10.48550/arxiv.2310.18634openalex-snapshot
SSL Framework for Causal Inconsistency between Structures and Representations
inferredcites →https://doi.org/10.48550/arxiv.2312.04350openalex-snapshot
CLadder: Assessing Causal Reasoning in Language Models
inferredcites →https://doi.org/10.48550/arxiv.2312.14670openalex-snapshot
Zero-shot Causal Graph Extrapolation from Text via LLMs
inferredcites →https://doi.org/10.48550/arxiv.2401.00139openalex-snapshot
Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
inferredcites →https://doi.org/10.48550/arxiv.2402.01454openalex-snapshot
Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
inferredcites →https://doi.org/10.48550/arxiv.2402.03941openalex-snapshot
Discovering and Reasoning of Causality in the Hidden World with Large Language Models
inferredcites →https://doi.org/10.48550/arxiv.2402.11068openalex-snapshot
Large Language Models for Causal Discovery: Current Landscape and Future Directions
inferredcites →https://doi.org/10.48550/arxiv.2405.00622openalex-snapshot
Causal Evaluation of Language Models
inferredcites →https://doi.org/10.48550/arxiv.2407.10153openalex-snapshot
Look Within, Why LLMs Hallucinate: A Causal Perspective
inferredcites →https://doi.org/10.48550/arxiv.2410.15553openalex-snapshot
Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following
inferredcites →https://doi.org/10.48550/arxiv.2410.16676openalex-snapshot
CausalEval: Towards Better Causal Reasoning in Language Models
inferredcites →https://doi.org/10.5194/wcd-1-313-2020openalex-snapshot
Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks
inferredcites →https://doi.org/10.52202/075280-3496openalex-snapshot
Invariant Learning via Probability of Sufficient and Necessary Causes
inferredcites →https://doi.org/10.5465/amp.2012.0175openalex-snapshot
Attribution Theory in the Organizational Sciences: The Road Traveled and the Path Ahead
inferredcites →https://doi.org/10.5555/777092.777180openalex-snapshot
A general identification condition for causal effects
inferredcites →https://doi.org/10.63317/34bje4jp4zxaopenalex-snapshot
CRASS: A Novel Data Set and Benchmark to Test Counterfactual Reasoning of Large Language Models
inferredcites →https://doi.org/10.63317/3dhqzf3tvt2zopenalex-snapshot
GPTEval: A Survey on Assessments of ChatGPT and GPT-4
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