1 citations · 1 across the 7 of their papers we have counts for
9 papers
Capability-Driven Self-Evolution of Agent Memory
Yaoqi Chen, Yuru Feng, Qianxi Zhang +8
Memory self-evolution uses task feedback to iteratively improve executable memory programs that store and retrieve information from past interactions. Existing approaches typically…
Aker: Density-Aware Approximate Caching for Vector Search (Extended Version)
Sukjoon Oh, Minki Kang, Dohyun Kim +5
Disk-based approximate nearest neighbor search (ANNS) incurs high I/O overhead due to frequent disk accesses during index traversal. Approximate caching, which reuses the results o…
MESA:Task-Adaptive Multi-Structure Evidence Selection for Long-Horizon Agent Memory
Beidi Zhao, Yaoqi Chen, Yuru Feng +10
Long-horizon agents accumulate trajectories spanning hundreds of interleaved reasoning, action, and observation steps, where answering a query may depend on evidence buried far bac…
SkillHEX: Improving Agent Skills via Hypothesis-Driven Autonomous Exploration and Exploitation
Yuru Feng, Yaoqi Chen, Beidi Zhao +7
Although agent skills equip LLMs with reusable procedural knowledge, manual maintenance suffers from high costs, unscalability, and misalignment. Real-world deployments thus requir…
Beyond Semantic Organization: Memory as Execution State Management for Long-Horizon Agents
Yaoqi Chen, Haibin Lai, Yuru Feng +12
LLM-based agents increasingly tackle long-horizon tasks with interdependent decisions, where each action reshapes future constraints and intermediate errors can cascade. Existing R…
Unifying Sparse Attention with Hierarchical Memory for Scalable Long-Context LLM Serving
Zihan Zhao, Baotong Lu, Shengjie Lin +8
Long-context LLM serving is bottlenecked by the cost of attending over ever-growing KV caches. Dynamic sparse attention promises relief by accessing only a small, query-dependent s…
Scalable Distributed Vector Search via Accuracy Preserving Index Construction
Yuming Xu, Qianxi Zhang, Qi Chen +8
Scaling Approximate Nearest Neighbor Search (ANNS) to billions of vectors requires distributed indexes that balance accuracy, latency, and throughput. Yet existing index designs st…
Towards Efficient and Scalable Distributed Vector Search with RDMA
Xiangyu Zhi, Meng Chen, Xiao Yan +5
Similarity-based vector search facilitates many important applications such as search and recommendation but is limited by the memory capacity and bandwidth of a single machine due…
Towards Robustness: A Critique of Current Vector Database Assessments
Zikai Wang, Qianxi Zhang, Baotong Lu +2
Vector databases are critical infrastructure in AI systems, and average recall is the dominant metric for their evaluation. Both users and researchers rely on it to choose and opti…