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20212026
most citedKoLA: Carefully Benchmarking World Knowledge of Large Language Models

24 citations · 57 across the 26 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CL2024

Awaking the Slides: A Tuning-free and Knowledge-regulated AI Tutoring System via Language Model Coordination

Daniel Zhang-Li, Zheyuan Zhang, Jifan Yu +8

The vast pre-existing slides serve as rich and important materials to carry lecture knowledge. However, effectively leveraging lecture slides to serve students is difficult due to…

cs.CY2024★ 5 cited

From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents

Jifan Yu, Zheyuan Zhang, Daniel Zhang-li +30

Since the first instances of online education, where courses were uploaded to accessible and shared online platforms, this form of scaling the dissemination of human knowledge to r…

cs.CL2024★ 5 cited

R-Eval: A Unified Toolkit for Evaluating Domain Knowledge of Retrieval Augmented Large Language Models

Shangqing Tu, Yuanchun Wang, Jifan Yu +6

Large language models have achieved remarkable success on general NLP tasks, but they may fall short for domain-specific problems. Recently, various Retrieval-Augmented Large Langu…

cs.CL2024

Knowledge-to-Jailbreak: Investigating Knowledge-driven Jailbreaking Attacks for Large Language Models

Shangqing Tu, Zhuoran Pan, Wenxuan Wang +6

Large language models (LLMs) have been increasingly applied to various domains, which triggers increasing concerns about LLMs' safety on specialized domains, e.g. medicine. Despite…

cs.CL2024

DICE: Detecting In-distribution Contamination in LLM's Fine-tuning Phase for Math Reasoning

Shangqing Tu, Kejian Zhu, Yushi Bai +3

The advancement of large language models (LLMs) relies on evaluation using public benchmarks, but data contamination can lead to overestimated performance. Previous researches focu…

cs.CL2024★ 4 cited

SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking

Yuanchun Wang, Jifan Yu, Zijun Yao +13

Applying large language models (LLMs) for academic API usage shows promise in reducing researchers' academic information seeking efforts. However, current LLM API-using methods str…