2 citations · 3 across the 10 of their papers we have counts for
10 papers
Agents-K1: Towards Agent-native Knowledge Orchestration
Zongsheng Cao, Bihao Zhan, Jinxin Shi +25
Current LLM-based research agents have advanced through agent orchestration, yet largely overlook scientific knowledge orchestration. Existing works often reduce papers to abstract…
Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
Lei Bai, Zongsheng Cao, Yang Chen +50
We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We investigate agent-horizon scaling…
FlowRAG: Synergizing Explicit Reasoning via Frequency-Aware Multi-Granularity Graph Flow
Bihao Zhan, Zongsheng Cao, Jie Zhou +2
Graph-based retrieval-augmented generation (GraphRAG) is effective for knowledge-intensive and multi-hop query tasks; however, many existing methods primarily seed entity-based gra…
MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery
Shangheng Du, Xiangchao Yan, Jinxin Shi +13
Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE), where sustained self-evolution…
PurifyGen: A Risk-Discrimination and Semantic-Purification Model for Safe Text-to-Image Generation
Zongsheng Cao, Yangfan He, Anran Liu +3
Recent advances in diffusion models have notably enhanced text-to-image (T2I) generation quality, but they also raise the risk of generating unsafe content. Traditional safety meth…
TV-RAG: A Temporal-aware and Semantic Entropy-Weighted Framework for Long Video Retrieval and Understanding
Zongsheng Cao, Yangfan He, Anran Liu +3
Large Video Language Models (LVLMs) have rapidly emerged as the focus of multimedia AI research. Nonetheless, when confronted with lengthy videos, these models struggle: their temp…
CoFi-Dec: Hallucination-Resistant Decoding via Coarse-to-Fine Generative Feedback in Large Vision-Language Models
Zongsheng Cao, Yangfan He, Anran Liu +3
Large Vision-Language Models (LVLMs) have achieved impressive progress in multi-modal understanding and generation. However, they still tend to produce hallucinated content that is…
CSGNN: Conquering Noisy Node labels via Dynamic Class-wise Selection
Yifan Li, Zhen Tan, Kai Shu +3
Graph Neural Networks (GNNs) have emerged as a powerful tool for representation learning on graphs, but they often suffer from overfitting and label noise issues, especially when t…
Geometry Interaction Knowledge Graph Embeddings
Zongsheng Cao, Qianqian Xu, Zhiyong Yang +2
Knowledge graph (KG) embeddings have shown great power in learning representations of entities and relations for link prediction tasks. Previous work usually embeds KGs into a sing…
ER: Equivariance Regularizer for Knowledge Graph Completion
Zongsheng Cao, Qianqian Xu, Zhiyong Yang +1
Tensor factorization and distanced based models play important roles in knowledge graph completion (KGC). However, the relational matrices in KGC methods often induce a high model…