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20242026
most citedGraph-of-Skills: Dependency-Aware Structural Retrieval for Massive Agent Skills

1 citations · 1 across the 8 of their papers we have counts for

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cs.CL2026

CiteAudit: You Cited It, But Did You Read It? A Benchmark for Verifying Scientific References in the LLM Era

Kaiwen Shi, Weixiang Sun, Zheyuan Zhang +3

Scientific research relies on citation integrity, yet large language models (LLMs) have introduced a critical risk: fabricated references that appear plausible but correspond to no…

cs.CL2026

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Zhengqing Yuan, Hanchi Sun, Lichao Sun +1

We present MegaTrain, a memory-centric system that efficiently trains 100B+ parameter large language models at full precision on a single GPU. Unlike traditional GPU-centric system…

cs.CL2026

MedGPT-oss: Training a General-Purpose Vision-Language Model for Biomedicine

Kai Zhang, Zhengqing Yuan, Cheng Peng +10

Biomedical multimodal assistants have the potential to unify radiology, pathology, and clinical-text reasoning, yet a critical deployment gap remains: top-performing systems are ei…

cs.CL2025

EfficientLLM: Efficiency in Large Language Models

Zhengqing Yuan, Weixiang Sun, Yixin Liu +13

Large Language Models (LLMs) have driven significant progress, yet their growing parameter counts and context windows incur prohibitive compute, energy, and monetary costs. We intr…

cs.CL2024

Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Yue Huang, Zhengqing Yuan, Yujun Zhou +8

Large Language Models (LLMs) are increasingly employed for simulations, enabling applications in role-playing agents and Computational Social Science (CSS). However, the reliabilit…