activity
20222026
most citedAssessing and Understanding Creativity in Large Language Models

35 citations · 84 across the 37 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

Kimi K3: Open Frontier Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +398

We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2024

Ex3: Automatic Novel Writing by Extracting, Excelsior and Expanding

Lei Huang, Jiaming Guo, Guanhua He +5

Generating long-term texts such as novels using artificial intelligence has always been a challenge. A common approach is to use large language models (LLMs) to construct a hierarc…

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.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…

cs.CL2023★ 1 cited

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…