Cover Image

Bayesian Statistical Modeling with Predictors from LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Franke, Michael, Tsvilodub, Polina, Carcassi, Fausto
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Cognitive Modeling with Scaffolded LLMs: A Case Study of Referential Expression Generation
by: Tsvilodub, Polina, et al.
Published: (2024)

Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering
by: Tsvilodub, Polina, et al.
Published: (2025)

Predictions from language models for multiple-choice tasks are not robust under variation of scoring methods
by: Tsvilodub, Polina, et al.
Published: (2024)

On Emergent Social World Models -- Evidence for Functional Integration of Theory of Mind and Pragmatic Reasoning in Language Models
by: Tsvilodub, Polina, et al.
Published: (2026)

Act or Clarify? Modeling Sensitivity to Uncertainty and Cost in Communication
by: Tsvilodub, Polina, et al.
Published: (2026)

Experimental Pragmatics with Machines: Testing LLM Predictions for the Inferences of Plain and Embedded Disjunctions
by: Tsvilodub, Polina, et al.
Published: (2024)

Non-literal Understanding of Number Words by Language Models
by: Tsvilodub, Polina, et al.
Published: (2025)

LLMs are Not Just Next Token Predictors
by: Downes, Stephen M., et al.
Published: (2024)

Readability Formulas, Systems and LLMs are Poor Predictors of Reading Ease
by: Klein, Keren Gruteke, et al.
Published: (2025)

The Statistical Signature of LLMs
by: Hadad, Ortal, et al.
Published: (2026)

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics
by: Riegler, Michael A., et al.
Published: (2025)

KoRe: Compact Knowledge Representations for Large Language Models
by: Cavicchini, Davide, et al.
Published: (2026)

Signatures of human-like processing in Transformer forward passes
by: Hu, Jennifer, et al.
Published: (2025)

A Statistical Analysis of LLMs' Self-Evaluation Using Proverbs
by: Sonoda, Ryosuke, et al.
Published: (2024)

Agent-based imitation dynamics can yield efficiently compressed population-level vocabularies
by: Imel, Nathaniel, et al.
Published: (2026)

Temporal Predictors of Outcome in Reasoning Language Models
by: David, Joey
Published: (2025)

BASIL: Bayesian Assessment of Sycophancy in LLMs
by: Atwell, Katherine, et al.
Published: (2025)

The Rarity Blind Spot: A Framework for Evaluating Statistical Reasoning in LLMs
by: Maekawa, Seiji, et al.
Published: (2025)

Semantic Scaling: Bayesian Ideal Point Estimates with Large Language Models
by: Burnham, Michael
Published: (2024)

ALIEN: Aligned Entropy Head for Improving Uncertainty Estimation of LLMs
by: Zabolotnyi, Artem, et al.
Published: (2025)

Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
by: Proskura, Polina, et al.
Published: (2024)

Automated Statistical Model Discovery with Language Models
by: Li, Michael Y., et al.
Published: (2024)

SPIKE-RL: Video-LLMs meet Bayesian Surprise
by: Ravi, Sahithya, et al.
Published: (2025)

Learning Next Action Predictors from Human-Computer Interaction
by: Shaikh, Omar, et al.
Published: (2026)

LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet?
by: Gupta, Rushil, et al.
Published: (2025)

2-Step Agent: A Framework for the Interaction of a Decision Maker with AI Decision Support
by: Nyberg, Otto, et al.
Published: (2026)

Large Language Models as Interpolated and Extrapolated Event Predictors
by: Zhang, Libo, et al.
Published: (2024)

BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design
by: Choudhury, Deepro, et al.
Published: (2025)

Understanding the Emergence of Seemingly Useless Features in Next-Token Predictors
by: Rofin, Mark, et al.
Published: (2026)

Are LLMs Models of Distributional Semantics? A Case Study on Quantifiers
by: Enyan, Zhang, et al.
Published: (2024)

Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
by: Su, Jingtong, et al.
Published: (2024)

MindShift: Analyzing Language Models' Reactions to Psychological Prompts
by: Vasiliuk, Anton, et al.
Published: (2025)

Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patterns
by: Xiao, Hanqi, et al.
Published: (2025)

Bayesian Optimization for Controlled Image Editing via LLMs
by: Cai, Chengkun, et al.
Published: (2025)

Large Language Models are Zero-Shot Next Location Predictors
by: Beneduce, Ciro, et al.
Published: (2024)

Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions
by: Zhang, Michael J. Q., et al.
Published: (2024)

Beyond Surface Statistics: Robust Conformal Prediction for LLMs via Internal Representations
by: Wang, Yanli, et al.
Published: (2026)

Large Language Models Are Bad Dice Players: LLMs Struggle to Generate Random Numbers from Statistical Distributions
by: Zhao, Minda, et al.
Published: (2026)

Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective
by: Gallego, Victor
Published: (2023)

Bayesian Preference Elicitation with Language Models
by: Handa, Kunal, et al.
Published: (2024)