most citedRefiner: Restructure Retrieval Content Efficiently to Advance Question-Answering Capabilities

6 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025★ 1 cited

Da Yu: Towards USV-Based Image Captioning for Waterway Surveillance and Scene Understanding

Runwei Guan, Ningwei Ouyang, Tianhao Xu +10

Automated waterway environment perception is crucial for enabling unmanned surface vessels (USVs) to understand their surroundings and make informed decisions. Most existing waterw…

cs.CL2025★ 1 cited

Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking

Yijie Xu, Aiwei Liu, Xuming Hu +2

As open-source large language models (LLMs) like Llama3 become more capable, it is crucial to develop watermarking techniques to detect their potential misuse. Existing watermarkin…

cs.LG2025★ 1 cited

OneForecast: A Universal Framework for Global and Regional Weather Forecasting

Yuan Gao, Hao Wu, Ruiqi Shu +11

Accurate weather forecasts are important for disaster prevention, agricultural planning, etc. Traditional numerical weather prediction (NWP) methods offer physically interpretable…

cs.CL2024

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection

Yibo Yan, Shen Wang, Jiahao Huo +13

As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particularly promising, especially in addr…

cs.CL2024★ 6 cited

Refiner: Restructure Retrieval Content Efficiently to Advance Question-Answering Capabilities

Zhonghao Li, Xuming Hu, Aiwei Liu +3

Large Language Models (LLMs) are limited by their parametric knowledge, leading to hallucinations in knowledge-extensive tasks. To address this, Retrieval-Augmented Generation (RAG…