activity
20192026
most citedAssessing and Understanding Creativity in Large Language Models

35 citations · 56 across the 26 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

World-Consistent Data Generation for Vision-and-Language Navigation

Yu Zhong, Rui Zhang, Zihao Zhang +9

Vision-and-Language Navigation (VLN) is a challenging task that requires an agent to navigate through photorealistic environments following natural-language instructions. One main…

cs.PL2024★ 5 cited

CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization

Yang Zhao, Di Huang, Chongxiao Li +14

The design flow of processors, particularly in hardware description languages (HDL) like Verilog and Chisel, is complex and costly. While recent advances in large language models (…

cs.CL2024

InverseCoder: Self-improving Instruction-Tuned Code LLMs with Inverse-Instruct

Yutong Wu, Di Huang, Wenxuan Shi +13

Recent advancements in open-source code large language models (LLMs) have been driven by fine-tuning on the data generated from powerful closed-source LLMs, which are expensive to…

cs.AI2024

Luban: Building Open-Ended Creative Agents via Autonomous Embodied Verification

Yuxuan Guo, Shaohui Peng, Jiaming Guo +15

Building open agents has always been the ultimate goal in AI research, and creative agents are the more enticing. Existing LLM agents excel at long-horizon tasks with well-defined…

cs.CL2024★ 35 cited

Assessing and Understanding Creativity in Large Language Models

Yunpu Zhao, Rui Zhang, Wenyi Li +10

In the field of natural language processing, the rapid development of large language model (LLM) has attracted more and more attention. LLMs have shown a high level of creativity i…