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20202026
most citedLogical Reasoning in Large Language Models: A Survey

5 citations · 10 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

From 0-Order Selection to 2-Order Judgment: Combinatorial Hardening Exposes Compositional Failures in Frontier LLMs

Hanmeng Liu, Shichao Weng, Xiulai Liu +3

Multiple-choice reasoning benchmarks face dual challenges: rapid saturation from advancing models and data contamination that undermines static evaluations. Ad-hoc hardening method…

cs.CL2024

Break the Chain: Large Language Models Can be Shortcut Reasoners

Mengru Ding, Hanmeng Liu, Zhizhang Fu +3

Recent advancements in Chain-of-Thought (CoT) reasoning utilize complex modules but are hampered by high token consumption, limited applicability, and challenges in reproducibility…

cs.CL2023

GLoRE: Evaluating Logical Reasoning of Large Language Models

Hanmeng liu, Zhiyang Teng, Ruoxi Ning +4

Large language models (LLMs) have shown significant general language understanding abilities. However, there has been a scarcity of attempts to assess the logical reasoning capacit…

cs.CL2023106 cited

Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4

Hanmeng Liu, Ruoxi Ning, Zhiyang Teng +3

Harnessing logical reasoning ability is a comprehensive natural language understanding endeavor. With the release of Generative Pretrained Transformer 4 (GPT-4), highlighted as "ad…

cs.CL2023

LogiCoT: Logical Chain-of-Thought Instruction-Tuning

Hanmeng Liu, Zhiyang Teng, Leyang Cui +3

Generative Pre-trained Transformer 4 (GPT-4) demonstrates impressive chain-of-thought reasoning ability. Recent work on self-instruction tuning, such as Alpaca, has focused on enha…

cs.CL2021

Solving Aspect Category Sentiment Analysis as a Text Generation Task

Jian Liu, Zhiyang Teng, Leyang Cui +2

Aspect category sentiment analysis has attracted increasing research attention. The dominant methods make use of pre-trained language models by learning effective aspect category-s…