Language and Experience: A Computational Model of Social Learning in Complex Tasks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Colas, Cédric, Mills, Tracey, Prystawski, Ben, Tessler, Michael Henry, Goodman, Noah, Andreas, Jacob, Tenenbaum, Joshua
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scaling up the think-aloud method
by: Wurgaft, Daniel, et al.
Published: (2025)

Code-enabled language models can outperform reasoning models on diverse tasks
by: Zhang, Cedegao E., et al.
Published: (2025)

Policy Learning with a Language Bottleneck
by: Srivastava, Megha, et al.
Published: (2024)

Loose LIPS Sink Ships: Asking Questions in Battleship with Language-Informed Program Sampling
by: Grand, Gabriel, et al.
Published: (2024)

Self-Steering Language Models
by: Grand, Gabriel, et al.
Published: (2025)

From Next-Token to Mathematics: The Learning Dynamics of Mathematical Reasoning in Language Models
by: Mishra, Shubhra, et al.
Published: (2024)

Shoot First, Ask Questions Later? Building Rational Agents that Explore and Act Like People
by: Grand, Gabriel, et al.
Published: (2025)

What Makes a Maze Look Like a Maze?
by: Hsu, Joy, et al.
Published: (2024)

Large Language Model Reasoning Failures
by: Song, Peiyang, et al.
Published: (2026)

Evaluating and Optimizing Educational Content with Large Language Model Judgments
by: He-Yueya, Joy, et al.
Published: (2024)

Lossy communication constrains iterated learning
by: Prystawski, Ben, et al.
Published: (2025)

Is Child-Directed Speech Effective Training Data for Language Models?
by: Feng, Steven Y., et al.
Published: (2024)

LILO: Learning Interpretable Libraries by Compressing and Documenting Code
by: Grand, Gabriel, et al.
Published: (2023)

CriticAL: Critic Automation with Language Models
by: Li, Michael Y., et al.
Published: (2024)

STaR-GATE: Teaching Language Models to Ask Clarifying Questions
by: Andukuri, Chinmaya, et al.
Published: (2024)

Value Profiles for Encoding Human Variation
by: Sorensen, Taylor, et al.
Published: (2025)

Learning Linear Attention in Polynomial Time
by: Yau, Morris, et al.
Published: (2024)

CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning
by: Nasvytis, Linas, et al.
Published: (2026)

Training Language Models to Explain Their Own Computations
by: Li, Belinda Z., et al.
Published: (2025)

Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind
by: Ying, Lance, et al.
Published: (2024)

Pretrained Generative Language Models as General Learning Frameworks for Sequence-Based Tasks
by: Fauber, Ben
Published: (2024)

Grounding Language about Belief in a Bayesian Theory-of-Mind
by: Ying, Lance, et al.
Published: (2024)

ComplexityNet: Increasing LLM Inference Efficiency by Learning Task Complexity
by: Bae, Henry, et al.
Published: (2023)

Hypothesis Search: Inductive Reasoning with Language Models
by: Wang, Ruocheng, et al.
Published: (2023)

Stream of Search (SoS): Learning to Search in Language
by: Gandhi, Kanishk, et al.
Published: (2024)

Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models
by: He-Yueya, Joy, et al.
Published: (2024)

Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning
by: Zhi-Xuan, Tan, et al.
Published: (2024)

Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models
by: Kim, Hyunwoo, et al.
Published: (2025)

Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
by: Zelikman, Eric, et al.
Published: (2024)

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models
by: Wong, Lionel, et al.
Published: (2025)

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks
by: Wu, Zhaofeng, et al.
Published: (2023)

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

LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers
by: Olausson, Theo X., et al.
Published: (2023)

Fast-Slow-Thinking: Complex Task Solving with Large Language Models
by: Sun, Yiliu, et al.
Published: (2025)

Establishing Task Scaling Laws via Compute-Efficient Model Ladders
by: Bhagia, Akshita, et al.
Published: (2024)

Context informs pragmatic interpretation in vision-language models
by: Tan, Alvin Wei Ming, et al.
Published: (2025)

ExpNote: Black-box Large Language Models are Better Task Solvers with Experience Notebook
by: Sun, Wangtao, et al.
Published: (2023)

A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models
by: Eisape, Tiwalayo, et al.
Published: (2023)

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

Evidence of Phase Transitions in Small Transformer-Based Language Models
by: Hong, Noah, et al.
Published: (2025)