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most citedOceanGPT: A Large Language Model for Ocean Science Tasks

10 citations · 24 across the 9 of their papers we have counts for

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cs.CL2025

BeyondBench: Contamination-Resistant Evaluation of Reasoning in Language Models

Gaurav Srivastava, Aafiya Hussain, Zhenyu Bi +5

Evaluating language models fairly is increasingly difficult as static benchmarks risk contamination by training data, obscuring whether models truly reason or recall. We introduce…

cs.CL2025

Spatial Knowledge Graph-Guided Multimodal Synthesis

Yida Xue, Zhen Bi, Jinnan Yang +5

Recent advances in Multimodal Large Language Models (MLLMs) have significantly enhanced their capabilities; however, their spatial perception abilities remain a notable limitation.…

cs.CL2024★ 1 cited

EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models

Yixin Ou, Ningyu Zhang, Honghao Gui +9

In recent years, instruction tuning has gained increasing attention and emerged as a crucial technique to enhance the capabilities of Large Language Models (LLMs). To construct hig…

cs.CL2023★ 10 cited

OceanGPT: A Large Language Model for Ocean Science Tasks

Zhen Bi, Ningyu Zhang, Yida Xue +4

Ocean science, which delves into the oceans that are reservoirs of life and biodiversity, is of great significance given that oceans cover over 70% of our planet's surface. Recentl…

cs.CL2023★ 2 cited

When Do Program-of-Thoughts Work for Reasoning?

Zhen Bi, Ningyu Zhang, Yinuo Jiang +3

In the realm of embodied artificial intelligence, the reasoning capabilities of Large Language Models (LLMs) play a pivotal role. Although there are effective methods like program-…

cs.CL2023★ 8 cited

CodeKGC: Code Language Model for Generative Knowledge Graph Construction

Zhen Bi, Jing Chen, Yinuo Jiang +4

Current generative knowledge graph construction approaches usually fail to capture structural knowledge by simply flattening natural language into serialized texts or a specificati…