Image de couverture de livre

Lost in the Logic: An Evaluation of Large Language Models' Reasoning Capabilities on LSAT Logic Games

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Malik, Saumya
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models
par: Parmar, Mihir, et autres
Publié: (2024)

LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models
par: Gui, Jiayi, et autres
Publié: (2024)

GLoRE: Evaluating Logical Reasoning of Large Language Models
par: liu, Hanmeng, et autres
Publié: (2023)

Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities
par: Hua, Wenyue, et autres
Publié: (2024)

LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models
par: Wan, Yuxuan, et autres
Publié: (2024)

Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding
par: Li, Yanda, et autres
Publié: (2024)

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
par: Chung, Tsz Ting, et autres
Publié: (2025)

Logical Reasoning in Large Language Models: A Survey
par: Liu, Hanmeng, et autres
Publié: (2025)

Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models
par: Pirozelli, Paulo, et autres
Publié: (2023)

Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
par: Xu, Fangzhi, et autres
Publié: (2023)

Do Large Language Models Excel in Complex Logical Reasoning with Formal Language?
par: Jiang, Jin, et autres
Publié: (2025)

Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models
par: Liu, Yinhong, et autres
Publié: (2024)

Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models
par: Patel, Nisarg, et autres
Publié: (2024)

LogicTree: Structured Proof Exploration for Coherent and Rigorous Logical Reasoning with Large Language Models
par: He, Kang, et autres
Publié: (2025)

Evaluating Consistency and Reasoning Capabilities of Large Language Models
par: Saxena, Yash, et autres
Publié: (2024)

Logic Contrastive Reasoning with Lightweight Large Language Model for Math Word Problems
par: Kai, Ding, et autres
Publié: (2024)

Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
par: Chen, Jiangjie, et autres
Publié: (2025)

LogicSkills: A Structured Benchmark for Formal Reasoning in Large Language Models
par: Rabern, Brian, et autres
Publié: (2026)

Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models
par: Luo, Man, et autres
Publié: (2023)

Improving Symbolic Translation of Language Models for Logical Reasoning
par: Thatikonda, Ramya Keerthy, et autres
Publié: (2026)

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

ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning
par: Luo, Linhao, et autres
Publié: (2023)

A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning
par: Hong, Ruixin, et autres
Publié: (2023)

Assessing and Enhancing the Robustness of Large Language Models with Task Structure Variations for Logical Reasoning
par: Bao, Qiming, et autres
Publié: (2023)

Transformer-based Language Models for Reasoning in the Description Logic ALCQ
par: Poulis, Angelos, et autres
Publié: (2024)

Language Models and Logic Programs for Trustworthy Tax Reasoning
par: Jurayj, William, et autres
Publié: (2025)

CLOMO: Counterfactual Logical Modification with Large Language Models
par: Huang, Yinya, et autres
Publié: (2023)

Normative Reasoning in Large Language Models: A Comparative Benchmark from Logical and Modal Perspectives
par: Ozeki, Kentaro, et autres
Publié: (2025)

JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models
par: Chen, Michael K., et autres
Publié: (2025)

MultiZebraLogic: A Multilingual Logical Reasoning Benchmark
par: Bruun, Sofie Helene, et autres
Publié: (2025)

SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
par: Liu, Junteng, et autres
Publié: (2025)

ReportLogic: Evaluating Logical Quality in Deep Research Reports
par: Zhao, Jujia, et autres
Publié: (2026)

Reasoning Capabilities of Large Language Models. Lessons Learned from General Game Playing
par: Świechowski, Maciej, et autres
Publié: (2026)

Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
par: Bao, Qiming, et autres
Publié: (2023)

Evaluating Interventional Reasoning Capabilities of Large Language Models
par: Kasetty, Tejas, et autres
Publié: (2024)

Do Large Language Models Understand Logic or Just Mimick Context?
par: Yan, Junbing, et autres
Publié: (2024)

DateLogicQA: Benchmarking Temporal Biases in Large Language Models
par: Bhatia, Gagan, et autres
Publié: (2024)

Towards Logically Sound Natural Language Reasoning with Logic-Enhanced Language Model Agents
par: Mensfelt, Agnieszka, et autres
Publié: (2024)

Reasoning Capabilities of Large Language Models on Dynamic Tasks
par: Wong, Annie, et autres
Publié: (2025)

Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation
par: Huang, Xu, et autres
Publié: (2024)