Imagen de Portada

Optimizing Language Models for Human Preferences is a Causal Inference Problem

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lin, Victoria, Ben-Michael, Eli, Morency, Louis-Philippe
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Computation and Language Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Omitted Variable Bias in Language Models Under Distribution Shift
por: Lin, Victoria, et al.
Publicado: (2026)

Isolated Causal Effects of Natural Language
por: Lin, Victoria, et al.
Publicado: (2024)

Proximal Causal Inference With Text Data
por: Chen, Jacob M., et al.
Publicado: (2024)

A Design-based Solution for Causal Inference with Text: Can a Language Model Be Too Large?
por: Tierney, Graham, et al.
Publicado: (2025)

CARL-GT: Evaluating Causal Reasoning Capabilities of Large Language Models
por: Tu, Ruibo, et al.
Publicado: (2024)

Causal Inference on Outcomes Learned from Text
por: Modarressi, Iman, et al.
Publicado: (2025)

Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models
por: Zhang, Yuzhe, et al.
Publicado: (2024)

MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
por: Wang, Tianze, et al.
Publicado: (2025)

MuPlon: Multi-Path Causal Optimization for Claim Verification through Controlling Confounding
por: Guo, Hanghui, et al.
Publicado: (2025)

End-To-End Causal Effect Estimation from Unstructured Natural Language Data
por: Dhawan, Nikita, et al.
Publicado: (2024)

Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
por: Cai, Hengrui, et al.
Publicado: (2023)

Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models
por: Egami, Naoki, et al.
Publicado: (2023)

CLEAR: Can Language Models Really Understand Causal Graphs?
por: Chen, Sirui, et al.
Publicado: (2024)

Language Models as Causal Effect Generators
por: Bynum, Lucius E. J., et al.
Publicado: (2024)

The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study
por: Lin, Victoria, et al.
Publicado: (2026)

Social Caption: Evaluating Social Understanding in Multimodal Models
por: Thumu, Bhaavanaa, et al.
Publicado: (2026)

LIDS: LLM Summary Inference Under the Layered Lens
por: Park, Dylan, et al.
Publicado: (2026)

Robust Detection of Watermarks for Large Language Models Under Human Edits
por: Li, Xiang, et al.
Publicado: (2024)

Causal Representation Learning from Multimodal Clinical Records under Non-Random Modality Missingness
por: Liang, Zihan, et al.
Publicado: (2025)

Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept
por: Trilla, Alexandre, et al.
Publicado: (2024)

Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
por: Kıcıman, Emre, et al.
Publicado: (2023)

TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model
por: Wang, Yue, et al.
Publicado: (2024)

Social Genome: Grounded Social Reasoning Abilities of Multimodal Models
por: Mathur, Leena, et al.
Publicado: (2025)

Optimal Estimation of Watermark Proportions in Hybrid AI-Human Texts
por: Li, Xiang, et al.
Publicado: (2025)

Hierarchical Causal Models
por: Weinstein, Eli N., et al.
Publicado: (2024)

Text Rationalization for Robust Causal Effect Estimation
por: Zhang, Lijinghua, et al.
Publicado: (2025)

A Causal Lens for Evaluating Faithfulness Metrics
por: Zaman, Kerem, et al.
Publicado: (2025)

RCT Rejection Sampling for Causal Estimation Evaluation
por: Keith, Katherine A., et al.
Publicado: (2023)

Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions
por: Mathur, Leena, et al.
Publicado: (2024)

ALCM: Autonomous LLM-Augmented Causal Discovery Framework
por: Khatibi, Elahe, et al.
Publicado: (2024)

Bayesian Inference for PDE-based Inverse Problems using the Optimization of a Discrete Loss
por: Amoudruz, Lucas, et al.
Publicado: (2025)

IoT-LM: Large Multisensory Language Models for the Internet of Things
por: Mo, Shentong, et al.
Publicado: (2024)

Annotation Sensitivity: Training Data Collection Methods Affect Model Performance
por: Kern, Christoph, et al.
Publicado: (2023)

Evaluating Interventional Reasoning Capabilities of Large Language Models
por: Kasetty, Tejas, et al.
Publicado: (2024)

Debiasing Watermarks for Large Language Models via Maximal Coupling
por: Xie, Yangxinyu, et al.
Publicado: (2024)

Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
por: Clivio, Oscar, et al.
Publicado: (2024)

Causal Inference Isn't Special: Why It's Just Another Prediction Problem
por: Fernández-Loría, Carlos
Publicado: (2025)

Random Text, Zipf's Law, Critical Length,and Implications for Large Language Models
por: Berman, Vladimir
Publicado: (2025)

Causal Inference for Human-Language Model Collaboration
por: Zhang, Bohan, et al.
Publicado: (2024)

Probabilistic Modelling is Sufficient for Causal Inference
por: Mlodozeniec, Bruno, et al.
Publicado: (2025)