most citedSuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20254 cited

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

P Team, Xinrun Du, Yifan Yao +94

Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…

eess.AS2025

YuE: Scaling Open Foundation Models for Long-Form Music Generation

Ruibin Yuan, Hanfeng Lin, Shuyue Guo +55

We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the…

cs.AI2025

Aligning Instruction Tuning with Pre-training

Yiming Liang, Tianyu Zheng, Xinrun Du +12

Instruction tuning enhances large language models (LLMs) to follow human instructions across diverse tasks, relying on high-quality datasets to guide behavior. However, these datas…

cs.CL2024

KARPA: A Training-free Method of Adapting Knowledge Graph as References for Large Language Model's Reasoning Path Aggregation

Siyuan Fang, Kaijing Ma, Tianyu Zheng +4

Large language models (LLMs) demonstrate exceptional performance across a variety of tasks, yet they are often affected by hallucinations and the timeliness of knowledge. Leveragin…

cs.CV2024

OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision

Cong Wei, Zheyang Xiong, Weiming Ren +3

Instruction-guided image editing methods have demonstrated significant potential by training diffusion models on automatically synthesized or manually annotated image editing pairs…