1 citations · 1 across the 11 of their papers we have counts for
12 papers
Inherit-MAS: Test-Time Evolution of Multi-Agent Systems through Workflow and Execution Inheritance
Songtao Wei, Yi Li, Zhichun Guo +1
Multi-agent systems (MAS) built from large language models coordinate specialized agents to tackle complex tasks, but effective workflows are difficult to design in advance. Test-t…
Jev-Mem: System-One-Controlled Agentic Memory for Efficient AI Agents
Dongming Jiang, Yi Li, Bingzhe Li
Agentic memory is becoming essential for long-horizon AI agents, yet many existing systems rely on autoregressive LLMs to control how memories are organized, retrieved, and used, p…
A Universal Context-Reuse Layer for Cross-Model KV Sharing
Yi Li, Dongming Jiang, Yi Zhao +1
Modern large language model (LLM) serving systems increasingly operate over repeated or shared context, yet each model typically performs its own prefill computation even when anot…
V-Mem: Modality-Routed Retrieval for Long-Term Multimodal Agentic Memory
Dingyi Kang, Dongming Jiang, Yi Li +2
Interaction between users and LLM agents is increasingly multimodal: conversations interleave text with images, and a later question may target either. Yet most agent memories are…
LAANN: I/O-Aware Look-Ahead Search for Disk-Based Approximate Nearest Neighbor Search
Dingyi Kang, Juncheng Yang, Bingzhe Li
Approximate nearest neighbor search (ANNS) is a fundamental primitive in large-scale retrieval, recommendation, and AI systems. As vector datasets grow to billions or even trillion…
DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs
Yi Li, Songtao Wei, Dongming Jiang +3
Multi-agent LLM systems improve reasoning by combining outputs from multiple agents, but interaction-heavy methods can introduce error propagation and high communication overhead.…
HAGE: Harnessing Agentic Memory via RL-Driven Weighted Graph Evolution
Dongming Jiang, Yi Li, Guanpeng Li +2
Memory retrieval in agentic large language model (LLM) systems is often treated as a static lookup problem, relying on flat vector search or fixed binary relational graphs. However…
LEAD: Length-Efficient Adaptive and Dynamic Reasoning for Large Language Models
Songtao Wei, Yi Li, Zhikai Li +7
Large reasoning models, such as OpenAI o1 and DeepSeek-R1, tend to become increasingly verbose as their reasoning capabilities improve. These inflated Chain-of-Thought (CoT) trajec…
Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations
Dongming Jiang, Yi Li, Songtao Wei +8
Agentic memory systems enable large language model (LLM) agents to maintain state across long interactions, supporting long-horizon reasoning and personalization beyond fixed conte…
MAGMA: A Multi-Graph based Agentic Memory Architecture for AI Agents
Dongming Jiang, Yi Li, Guanpeng Li +1
Memory-Augmented Generation (MAG) extends Large Language Models with external memory to support long-context reasoning, but existing approaches largely rely on semantic similarity…
Scalable Disk-Based Approximate Nearest Neighbor Search with Page-Aligned Graph
Dingyi Kang, Dongming Jiang, Hanshen Yang +2
Approximate Nearest Neighbor Search (ANNS), as the core of vector databases (VectorDBs), has become widely used in modern AI and ML systems, powering applications from information…
Analyzing 16,193 LLM Papers for Fun and Profits
Zhiqiu Xia, Lang Zhu, Bingzhe Li +5
Large Language Models (LLMs) are reshaping the landscape of computer science research, driving significant shifts in research priorities across diverse conferences and fields. This…