35 citations · 56 across the 26 of their papers we have counts for
5 papers · 1 filter
QiMeng-CodeV-SVA: Training Specialized LLMs for Hardware Assertion Generation via RTL-Grounded Bidirectional Data Synthesis
Yutong Wu, Chenrui Cao, Pengwei Jin +6
SystemVerilog Assertions (SVAs) are crucial for hardware verification. Recent studies leverage general-purpose LLMs to translate natural language properties to SVAs (NL2SVA), but t…
StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion
Yutong Wu, Di Huang, Ruosi Wan +8
Autoformalization aims to translate natural-language mathematical statements into a formal language. While LLMs have accelerated progress in this area, existing methods still suffe…
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…
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…
Self-driven Grounding: Large Language Model Agents with Automatical Language-aligned Skill Learning
Shaohui Peng, Xing Hu, Qi Yi +9
Large language models (LLMs) show their powerful automatic reasoning and planning capability with a wealth of semantic knowledge about the human world. However, the grounding probl…