activity
20232026
most citedTowards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning

17 citations · 24 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents

Minghang Zhu, Chuyang Wei, Junhao Xu +3

Deep research agents synthesize long-form reports by searching and reasoning over retrieved evidence. Reinforcement learning with rubric-based rewards improves these agents by opti…

cs.IR2026

OneRank: Unified Transformer-Native Ranking Architecture for Multi-Task Recommendation

Jiakai Tang, Sunhao Dai, Kun Wang +8

Multi-task learning (MTL) is essential in recommender systems to enable complementary learning among diverse user feedback. While modern industrial practices have shifted from DNNs…

cs.CL2026

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale

Ang Li, Ben Liu, Bin Han +215

Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…

cs.CL2024★ 2 cited

Towards Effective and Efficient Continual Pre-training of Large Language Models

Jie Chen, Zhipeng Chen, Jiapeng Wang +16

Continual pre-training (CPT) has been an important approach for adapting language models to specific domains or tasks. To make the CPT approach more traceable, this paper presents…

cs.IR2024★ 17 cited

Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning

Jiakai Tang, Sunhao Dai, Zexu Sun +6

In recent years, graph contrastive learning (GCL) has received increasing attention in recommender systems due to its effectiveness in reducing bias caused by data sparsity. Howeve…

cs.CL2024

YuLan: An Open-source Large Language Model

Yutao Zhu, Kun Zhou, Kelong Mao +35

Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many o…

cs.IR2023★ 5 cited

User Behavior Simulation with Large Language Model based Agents

Lei Wang, Jingsen Zhang, Hao Yang +11

Simulating high quality user behavior data has always been a fundamental problem in human-centered applications, where the major difficulty originates from the intricate mechanism…