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20232026
most citedEvaluation of OpenAI o1: Opportunities and Challenges of AGI

22 citations · 102 across the 15 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

Compositional Consistency-Guided Decoding for Three-Way Logical Question Answering

Tianyi Huang, Ming Hou, Jiaheng Su +2

Three-way logical question answering (QA) assigns one of , , or to a hypothesis given a premise set . We study this task as a com…

cs.CL2026

Reflections and New Directions for Human-Centered Large Language Models

Caleb Ziems, Dora Zhao, Rose E. Wang +55

Large Language Models (LLMs) are increasingly shaping the private and professional lives of users, with numerous applications in business, education, finance, healthcare, law, and…

cs.CL2026

PRISM: Probing Reasoning, Instruction, and Source Memory in LLM Hallucinations

Yuhe Wu, Guangyu Wang, Yuran Chen +6

As large language models (LLMs) evolve from conversational assistants into agents capable of handling complex tasks, they are increasingly deployed in high-risk domains. However, e…

cs.CL2024★ 1 cited

Legal Evalutions and Challenges of Large Language Models

Jiaqi Wang, Huan Zhao, Zhenyuan Yang +19

In this paper, we review legal testing methods based on Large Language Models (LLMs), using the OPENAI o1 model as a case study to evaluate the performance of large models in apply…

cs.CL2024★ 22 cited

Evaluation of OpenAI o1: Opportunities and Challenges of AGI

Tianyang Zhong, Zhengliang Liu, Yi Pan +74

This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, includi…

cs.CL2024★ 14 cited

Understanding LLMs: A Comprehensive Overview from Training to Inference

Yiheng Liu, Hao He, Tianle Han +18

The introduction of ChatGPT has led to a significant increase in the utilization of Large Language Models (LLMs) for addressing downstream tasks. There's an increasing focus on cos…