Cp-Agent

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8 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 32

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DAGent: Evaluate-then-Grow Planning for Deep Research Agents
Sep 30, 2026Hanwen Liu, Yuanfu Sun, Qiaoyu TanDeep Research Action-Conditioned Planning
New York University · New York University Shanghai
GitHarness: Git Init Your Harness Working Memory for Perpetual User Requirements
Sep 29, 2026Zhibang Yang, Xinke Jiang, Yuxuan Liu +9Collaboration Cp-Agent
National Engineering Research Center of Software Engineering, Peking University, Beijing, China · School of Computer Science, Peking University, Beijing, China · Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China +2
DexAgent: An Agentic Human2Sim2Robot Framework for Dexterous Manipulation with Self-Evolving Tool Library
Sep 28, 2026Youhui Wang, Yunzhu Li, Li Fei-Fei +2Human-To-Robot Transfer Humanoid Robotics
Stanford University · Columbia University
AgentWare: Automating the Lifecycle of Agentic Applications across the Edge-to-Cloud Continuum
Sep 28, 2026Michalis Kasioulis, Moysis Symeonides, George Pallis +1Agentic Deployments Edge Platforms
Department of Computer Science, University of Cyprus
Org-Agent: Beyond Personal Assistants Towards Organizational Agents
Sep 28, 2026Luyao Zhuang, Yujing Zhang, Zijin Hong +2Multi-Agent Orchestration Cp-Agent
The Department of Computing, The Hong Kong Polytechnic University, Hong Kong SAR
STR-Agent: An LLM-Driven Agent for QoS-Aware Routing in LEO Satellite Networks
Sep 17, 2026Bowen Lu, Mugen Peng, Yaohua Sun +3Low Earth Orbit Satellite Networks Cp-Agent
State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications
Memory Compression for High-Fanout Agent Sandboxes
Sep 12, 2026Mengming Li, Ceyu XU, Qijun Zhang +4Sandbox Task-Aware Compression
HKUST
K-Bench: A Benchmark for LLM Unlearning in Agentic Deployments
Sep 11, 2026Guangsheng Yu, Yanna Jiang, Qin Wang +2Large Language Model Unlearning Agentic Deployments
University of Technology Sydney, Australia · CSIRO, Australia
MedAgent-R1: Faithfulness-Aware Reinforcement Learning for Evidence-Grounded Medical Reasoning
Aug 31, 2026Jiangwang Chen, Chenghao Zhang, Hengxing CaiClinical Reasoning Training Evidence-Grounded Questions
Tsinghua University · DP Technology
VOS-Agent: The 1st Place Solution for the 8th LSVOS Challenge (MOSEv2 Track)
Aug 13, 2026Canyang Wu, Jinrong Zhang, Xusheng He +3Video Object Segmentation Neural Mask Estimation
Harbin Institute of Technology, Shenzhen · Nanyang Technological University · Shenzhen Loop Area Institute
GS-Agent: Creating 4D Physical Worlds With Generative Simulation
Jul 23, 2026Hongxin Zhang, Chunru Lin, Junyan Li +34D Generation Playable Video World Generation
University of Massachusetts Amherst · Genesis AI
SR-Agent: An Experience-Driven Agentic Framework for Post-Ranking Strategy Refinement in E-Commerce Recommendation
Jul 20, 2026Hanchen Yang, Kaiwen Yang, Junpeng Zhuang +7Agentic Commerce Cp-Agent
Kuaishou Technology, Beijing, China
MMAgent-R $^2$ : Learning to Rerank and Reject for Agentic mRAG
Jul 8, 2026Tao Zhang, Ziqi Zhang, Zongyang Ma +7Knowledge-Based Visual Question Answering Multimodal Retrieval Augmented Generation
State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA · School of Artificial Intelligence, University of Chinese Academy of Sciences · Beijing Key Laboratory of Super Intelligent Security of Multi-Modal Information +3
CPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association
Jun 26, 2026Zuoou Li, Wenlong Zhao, Kelly Yu +5Phenotypes Cardiovascular Risk Prediction
Department of Mechanical Engineering, University College London, London, UK · CSIG Group, Tencent, Beijing, China · Department of Computing, Imperial College London, London, UK +5
ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection
Jun 23, 2026Chenhao Dang, Dantong Zhu, Jun Yang +2Misinformation Detection Reference-Guided Multimodal In-Context Verification
Shanghai Jiaotong University · Shanghai Artificial Intelligence Laboratory · Central South University +2
S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence
Jun 18, 2026Yalun Dai, Hao Li, Shulin Tian +10Spatial Reasoning Cp-Agent
1NTU · ★Ropedia · 2THU +2
DRFLOW: A Deep Research Benchmark for Personalized Workflow Prediction
Jun 16, 2026Md Tawkat Islam Khondaker, Raymond Li, Muhammad Abdul-Mageed +2Deep Research Agentic Workflow Design
Canada Research Chair in NLP and ML · The University of British Columbia
EChO-Agent: Evidence Chain Orchestration Agent for Audio Reasoning
Jun 13, 2026Siyuan Zhang, Jian Zong, Junyu Wang +7Audio Understanding Audio Understanding
School of Artificial Intelligence, Tianjin University, Tianjin, China
AliyunConsoleAgent: Training Web Agents in Real-World Cloud Environments via Distillation and Reinforcement Learning
Jun 8, 2026Bojie Rong, Zheyu Shen, Qiaoping Wang +7Cloud Cp-Agent
Alibaba Cloud China
MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation
Jun 3, 2026Deguo Xia, Zihan Li, Haochen Zhao +6Lane-Level Map Generation Autonomous Driving
Tsinghua University Baidu Beijing, China · University of Macau Macao, China · Institute of Information Engineering, Chinese Academy of Sciences Beijing, China +2
CP-Agent: Context-Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations
Jun 2, 2026Yuxin Zhang, Yiyao Li, Ping Shu Ho +3Drug Discovery Multimodal Agents
Department of Electrical and Computer Engineering, The University of Hong Kong · School of Computing and Data Science, The University of Hong Kong · Nvidia AI Technology Center +2
APT-Agent: Automated Penetration Testing using Large Language Models
May 24, 2026William Guanting Li, Alsharif Abuadbba, Kristen Moore +1Penetration Testing Attacker Large Language Model
University of Queensland · University of Queensland Brisbane, Australia · CSIRO Data61 +2
CP-Agent: A Calibrated Risk-Controlled Agent for Feedback-Driven Competitive Programming
May 23, 2026Peisong Wang, Bowen Liu, Zehua Li +4Raw Judge Outputs Cp-Agent
The Hong Kong University of Science and Technology (Guangzhou) Guangzhou, China
R2V Agent: Teaching SLMs When to Ask for Help
May 15, 2026Raghu Vamshi Hemadri, Humaira Firdowse Mohammed, Rishabh Maheshwary +5Large Language Model Routing Cp-Agent
New York University Tandon School of Engineering · University of California, San Diego · ServiceNow Research +3
BootstrapAgent: Distilling Repository Setup into Reusable Agent Knowledge
May 15, 2026Sihan Fu, Oucheng Liu, Shiyuan Wang +2Repository-Level Code Understanding Cp-Agent
Zhejiang University · The Australian National University · Institute of Information Engineering, Chinese Academy of Sciences
Seg-Agent: Test-Time Multimodal Reasoning for Training-Free Language-Guided Segmentation
May 13, 2026Chao Hao, Jun Xu, Ji Du +6Multimodal Reasoning Multimodal Large Language Models
School of Computing and Information Technology, Great Bay University, Dongguan, Guangdong, 523000, China · Hangzhou International Innovation Institute, Beihang University, Hangzhou, 311115, China · Department of Computing, The Hong Kong Polytechnic University, Hong Kong
CAX-Agent: A Lightweight Agent Harness for Reliable APDL Automation
May 12, 2026Chenying Lin, Yichen Hai, Yi He +3Cp-Agent Agent Harness
Shanghai Ultradimension Technology Co., Ltd., Shanghai, China · College of Logistics Engineering, Shanghai Maritime University, Shanghai, 201306, China · School of Civil Aviation, Northwestern Polytechnical University, Xi’an 710072, China +3
PresentAgent-2: Towards Generalist Multimodal Presentation Agents
May 12, 2026Wei Wu, Ziyang Xu, Zeyu Zhang +2Video Agent Multimodal Agents
1Peking University · 2La Trobe University
RAT: RunAnyThing via Fully Automated Environment Configuration
Apr 25, 2026Renhong Huang, Dongdong Hua, Yifei Sun +4Repository-Level Code Understanding Coding Agents
Zhejiang University · Ant Group
BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software
Sep 27, 2025Zehua Zhang, Ati Priya Bajaj, Divij Handa +14Large Language Model Agents Open-Source
School of Computing and Augmented Intelligence, Arizona State University
AgentRM: Enhancing Agent Generalization with Reward Modeling
Feb 25, 2025Yu Xia, Jingru Fan, Weize Chen +7Large Language Model Agents Reward Functions
Department of Computer Science and Technology, Tsinghua University · Gaoling School of Artificial Intelligence, Renmin University of China
RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
Jun 11, 2024Wenjia Xu, Zijian Yu, Boyang Mu +3Remote Sensing Geospatial Reasoning
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China · City University of HongKong, Hong Kong 999077, China · School of Geographic Sciences, Hunan Normal University, Changsha 410081, China

Sep 30, 2026, cs.CLJ/K move · Enter open · S save

DAGent: Evaluate-then-Grow Planning for Deep Research Agents

Hanwen Liu, Yuanfu Sun, Qiaoyu Tan

New York University · New York University Shanghai

Deep Research Action-Conditioned Planning Model-Based Multi-Agent Systems Cp-Agent Planning

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Deep research tasks require agents to navigate large knowledge spaces, synthesize evidence across many sources, and adapt their plans as findings emerge. Directed acyclic graph (DAG)-based multi-agent systems suit this setting because they support parallel execution and isolate each sub-task within a focused dependency context. Yet existing DAG-based agents instantiate a task-level plan before execution and repair the graph only after failures or missing evidence are observed. This Plan-then-Patch strategy is brittle for deep research: the system commits most strongly when its evidence is weakest, and later revisions waste computation on branches that should not have been planned. We propose DAGent, a DAG-based multi-agent framework with Evaluate-then-Grow incremental planning: an Orchestrator grows the task graph one batch at a time, conditioning each expansion on confidence and uncertainty signals from completed nodes. A hierarchical context layer propagates compact QueryDocs by default while preserving full execution traces for on-demand recall. The recorded DAG topology admits structural RL signals that outcome-only recipes cannot define; DAGRPO, a GRPO adaptation, injects topology-conditioned credit on Executor rollouts and a structural compliance regularization on Orchestrator plans. Across BrowseComp-Plus, GAIA, and xbench-DeepSearch, DAGent surpasses the strongest open-source baseline by 5.3 / 5.8 / 2.0 points at the Qwen3-235B-A22B scale, and the lead replicates across four open-source backbones and extends to GPT-5 at 327K context. At the Qwen3-8B scale, DAGRPO improves over a same-budget outcome-only GRPO baseline by 3.0 average Pass@1 points. A same-architecture comparison shows that evidence-conditioned planning reaches higher accuracy at lower per-task token, tool-call, and step footprints than its Plan-then-Patch counterpart. Code: https://github.com/hanwenliu6825/DAGent

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Latest papers 32