Cover Image

Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Opedal, Andreas, Stolfo, Alessandro, Shirakami, Haruki, Jiao, Ying, Cotterell, Ryan, Schölkopf, Bernhard, Saparov, Abulhair, Sachan, Mrinmaya
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs
by: Opedal, Andreas, et al.
Published: (2024)

Are Language Models Efficient Reasoners? A Perspective from Logic Programming
by: Opedal, Andreas, et al.
Published: (2025)

Learning to Reason Efficiently with A* Post-Training
by: Opedal, Andreas, et al.
Published: (2026)

World Models for Math Story Problems
by: Opedal, Andreas, et al.
Published: (2023)

Probing for Arithmetic Errors in Language Models
by: Sun, Yucheng, et al.
Published: (2025)

What Do Language Models Learn in Context? The Structured Task Hypothesis
by: Li, Jiaoda, et al.
Published: (2024)

Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning
by: Sun, Yunxin, et al.
Published: (2025)

Fluid Representations in Reasoning Models
by: Kharlapenko, Dmitrii, et al.
Published: (2026)

Transformers Can Learn Connectivity in Some Graphs but Not Others
by: Roy, Amit, et al.
Published: (2025)

Language Models Might Not Understand You: Evaluating Theory of Mind via Story Prompting
by: Getachew, Nathaniel, et al.
Published: (2025)

Improving Large Language Model Safety with Contrastive Representation Learning
by: Simko, Samuel, et al.
Published: (2025)

Generalized Measures of Anticipation and Responsivity in Online Language Processing
by: Giulianelli, Mario, et al.
Published: (2024)

Efficiently Computing Susceptibility to Context in Language Models
by: Liu, Tianyu, et al.
Published: (2024)

Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis
by: Lyu, Zhiheng, et al.
Published: (2024)

Simulating Students or Sycophantic Problem Solving? On Misconception Faithfulness of LLM Simulators
by: Do, Heejin, et al.
Published: (2026)

A Transformer with Stack Attention
by: Li, Jiaoda, et al.
Published: (2024)

On the Emergence of Induction Heads for In-Context Learning
by: Musat, Tiberiu, et al.
Published: (2025)

Rethinking Easy-to-Hard: Limits of Curriculum Learning in Post-Training for Deductive Reasoning
by: Mordig, Maximilian, et al.
Published: (2026)

Exploring the Jungle of Bias: Political Bias Attribution in Language Models via Dependency Analysis
by: Jenny, David F., et al.
Published: (2023)

Dense SAE Latents Are Features, Not Bugs
by: Sun, Xiaoqing, et al.
Published: (2025)

Confidence Regulation Neurons in Language Models
by: Stolfo, Alessandro, et al.
Published: (2024)

Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation
by: Zengaffinen, Yanick, et al.
Published: (2026)

On the Role of Context in Reading Time Prediction
by: Opedal, Andreas, et al.
Published: (2024)

Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals
by: Ortu, Francesco, et al.
Published: (2024)

From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
by: Dinucu-Jianu, David, et al.
Published: (2025)

Pointwise Mutual Information as a Performance Gauge for Retrieval-Augmented Generation
by: Liu, Tianyu, et al.
Published: (2024)

Post-Training Language Models for Crosslingual Consistency
by: Liu, Tianyu, et al.
Published: (2026)

Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study
by: Stolfo, Alessandro
Published: (2024)

Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games
by: Piedrahita, David Guzman, et al.
Published: (2025)

Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents
by: Piatti, Giorgio, et al.
Published: (2024)

LLMs Are Prone to Fallacies in Causal Inference
by: Joshi, Nitish, et al.
Published: (2024)

AI-Assisted Human Evaluation of Machine Translation
by: Zouhar, Vilém, et al.
Published: (2024)

A Spatio-Temporal Point Process for Fine-Grained Modeling of Reading Behavior
by: Re, Francesco Ignazio, et al.
Published: (2025)

How to Select Datapoints for Efficient Human Evaluation of NLG Models?
by: Zouhar, Vilém, et al.
Published: (2025)

CausalCite: A Causal Formulation of Paper Citations
by: Kumar, Ishan, et al.
Published: (2023)

On Affine Homotopy between Language Encoders
by: Chan, Robin SM, et al.
Published: (2024)

Investigating the Zone of Proximal Development of Language Models for In-Context Learning
by: Cui, Peng, et al.
Published: (2025)

GPT-4 as a Homework Tutor can Improve Student Engagement and Learning Outcomes
by: Vanzo, Alessandro, et al.
Published: (2024)

Multilingual Performance Biases of Large Language Models in Education
by: Gupta, Vansh, et al.
Published: (2025)

Prefix Parsing is Just Parsing
by: Pasti, Clemente, et al.
Published: (2026)