activity
20232026
most citedSora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

105 citations · 129 across the 29 of their papers we have counts for

collaborators

30 papers

cs.AI2026

Dr. Claw: An AI Scientist Workspace for Vibe Research

Dingjie Song, Hanrong Zhang, Dawei Liu +10

Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, yet end-to-end research still fragments across chat tools, ID…

cs.AI2026

PreDiff-LM: Pretrained Discrete Masked Diffusion Language Modeling with Hybrid Attention

Zhengtao Yao, Runhao Li, Xupeng Chen +12

Discrete masked diffusion language models support bidirectional generation and infilling, but adapting pretrained autoregressive (AR) transformers requires reconciling causal pretr…

cs.AI2026

SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic Data

Wenjie Wang, Yue Huang, Zhengqing Yuan +6

As large language models (LLMs) are increasingly deployed in real-world applications, alignment is no longer governed by a single universal notion of safety or helpfulness, but ins…

cs.CV2026

Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?

Yichen Feng, Yuetai Li, Chunjiang Liu +14

Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of these applications require an expl…

cs.CL2026

NARRA-Gym for Evaluating Interactive Narrative Agents

Yue Huang, Yuchen Ma, Jiayi Ye +14

Interactive narrative tasks require LLMs to sustain a coherent, evolving story while adapting to a user over multiple turns. However, suitable benchmarks for this setting are limit…

cs.CL2026

PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models

Han Bao, Penghao Zhang, Yue Huang +9

Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability to comprehend and reason abou…

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.AI2026

Drift-Bench: Diagnosing Cooperative Breakdowns in LLM Agents under Input Faults via Multi-Turn Interaction

Han Bao, Zheyuan Zhang, Pengcheng Jing +3

As Large Language Models transition to autonomous agents, user inputs frequently violate cooperative assumptions (e.g., implicit intent, missing parameters, false presuppositions,…

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.OS2026

Horizon-LM: A RAM-Centric Architecture for LLM Training

Zhengqing Yuan, Lichao Sun, Yanfang Ye

The rapid growth of large language models (LLMs) has outpaced the evolution of single-GPU hardware, making model scale increasingly constrained by memory capacity rather than compu…

cs.RO2025

BLURR: A Boosted Low-Resource Inference for Vision-Language-Action Models

Xiaoyu Ma, Zhengqing Yuan, Zheyuan Zhang +3

Vision-language-action (VLA) models enable impressive zero shot manipulation, but their inference stacks are often too heavy for responsive web demos or high frequency robot contro…

cs.CV2025

3D4D: An Interactive, Editable, 4D World Model via 3D Video Generation

Yunhong He, Zhengqing Yuan, Zhengzhong Tu +2

We introduce 3D4D, an interactive 4D visualization framework that integrates WebGL with Supersplat rendering. It transforms static images and text into coherent 4D scenes through f…

cs.LG2025

Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use

Yiyang Li, Zehong Wang, Zhengqing Yuan +4

Illicit drug use among teenagers and young adults (TYAs) remains a pressing public health concern, with rising prevalence and long-term impacts on health and well-being. To detect…

cs.CL2025

NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answering

Kaiwen Shi, Zheyuan Zhang, Zhengqing Yuan +4

Diet plays a central role in human health, and Nutrition Question Answering (QA) offers a promising path toward personalized dietary guidance and the prevention of diet-related chr…

cs.CL2025

AgentRouter: A Knowledge-Graph-Guided LLM Router for Collaborative Multi-Agent Question Answering

Zheyuan Zhang, Kaiwen Shi, Zhengqing Yuan +6

Large language models (LLMs) and agent-based frameworks have advanced rapidly, enabling diverse applications. Yet, with the proliferation of models and agentic strategies, practiti…

cs.CL2025

Food4All: An Agentic Framework and Benchmark for Food Resource Navigation with Adaptive User Understanding

Yiyang Li, Weixiang Sun, Tianyi Ma +3

Food assistance referral requires conversational agents to translate underspecified, often noisy help-seeking dialogues into locally valid resource recommendations. We present Food…

cs.CL2025

ChemOrch: Empowering LLMs with Chemical Intelligence via Synthetic Instructions

Yue Huang, Zhengzhe Jiang, Xiaonan Luo +12

Empowering large language models (LLMs) with chemical intelligence remains a challenge due to the scarcity of high-quality, domain-specific instruction-response datasets and the mi…

cs.LG2025★ 3 cited

Graph Foundation Models: A Comprehensive Survey

Zehong Wang, Zheyuan Liu, Tianyi Ma +16

Graph-structured data pervades domains such as social networks, biological systems, knowledge graphs, and recommender systems. While foundation models have transformed natural lang…

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.AI2025

Reason Like a Radiologist: Chain-of-Thought and Reinforcement Learning for Verifiable Report Generation

Peiyuan Jing, Kinhei Lee, Zhenxuan Zhang +7

Radiology report generation is critical for efficiency but current models lack the structured reasoning of experts, hindering clinical trust and explainability by failing to link v…

cs.CL2024★ 1 cited

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…

cs.LG2024

MLP-KAN: Unifying Deep Representation and Function Learning

Yunhong He, Yifeng Xie, Zhengqing Yuan +1

Recent advancements in both representation learning and function learning have demonstrated substantial promise across diverse domains of artificial intelligence. However, the effe…

eess.IV2024★ 1 cited

TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation

Rong Zhou, Zhengqing Yuan, Zhiling Yan +7

Biomedical image segmentation is crucial for accurately diagnosing and analyzing various diseases. However, Convolutional Neural Networks (CNNs) and Transformers, the most commonly…