24 citations · 24 across the 8 of their papers we have counts for
10 papers
4DMemory: Benchmarking Long-Horizon Spatiotemporal Memory with Harness-Augmented Agents
Yanhao Jia, Yi Zhu, Yiran Zhong +7
Humans efficiently process multimodal streams spanning hours to years, building persistent, fine-grained spatiotemporal memories that support reasoning about and predicting long-ho…
Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents
Tingyu Qu, Weigao Sun, Yuecheng Liu +23
The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific discovery. This shift raises…
ProCredit: From Outcome Rewards to Progress Credit in Agentic Reinforcement Learning
Ming Ma, Yi Zhu, Yiran Zhong +7
Long-horizon agentic tasks require an agent to modify an environment through a sequence of tool calls, with success determined by the final state. The standard recipe assigns a sin…
Block-Sparse Attention with Semantic-Geometric Decoupled Routing
Xinwei Long, Weigao Sun, Weibo Gao +6
Long-context inference has become a defining capability of large language models, but exact dense attention remains costly due to its quadratic scaling with sequence length. Block-…
MobilePA-Bench: Benchmarking Mobile Planner Agents on Complex Real-World Tasks
Yi Zhu, Xiongwei Wu, Qiyi Wang +8
Mobile planning requires a central agent to coordinate tools, persistent user context, reusable procedures, and specialized sub-agents while adapting to execution feedback. Evaluat…
Omni-Decision: Evidence-Ledger Planning for Omni-Modal Agents
Ming Ma, Yi Zhu, Yiran Zhong +7
Omni-modal agents must seek evidence across video, audio, web pages, and computation to answer questions. Their main bottleneck is planning: noisy multimodal observations accumulat…
Covering the Unseen: Information Demand Coverage Optimization for Retrieval-Augmented Generation
Bingxue Zhang, Jianying Jia, Feida Zhu
Retrieval-augmented generation (RAG) typically treats context selection as ranking chunks against a single query embedding. This assumption breaks down for complex queries, such as…
LineageMark: Multi-user White-box Watermarking for Contribution Tracing in Model Derivation Chains
Bingxue Zhang, Xiaofeng Xu, Feida Zhu
In open large language model (LLM) ecosystems, models are frequently adapted across multiple domains and applications, forming multi-stage derivation chains. Consequently, tracking…
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data
Weiran Pan, Wei Wei, Feida Zhu +1
We propose a novel sample selection method for image classification in the presence of noisy labels. Existing methods typically consider small-loss samples as correctly labeled. Ho…
Knowledge Enhanced Multi-intent Transformer Network for Recommendation
Ding Zou, Wei Wei, Feida Zhu +3
Incorporating Knowledge Graphs into Recommendation has attracted growing attention in industry, due to the great potential of KG in providing abundant supplementary information and…