collaborators

14 papers

cs.CL2026

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers

Tao Feng, Fangxu Yu, Haozhen Zhang +9

No single large language model (LLM) is optimal across all queries and budget constraints, making model routing essential for cost-effective deployment. Existing routers adopt dive…

cs.LG2026

FusionFactory: Fusing LLM Capabilities with Multi-LLM Log Data

Tao Feng, Haozhen Zhang, Zijie Lei +5

The rapid advancement of large language models (LLMs) has created a diverse landscape of models, each excelling at different tasks. This diversity drives researchers to employ mult…

cs.CL2026

ExpGraph: Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents

Tao Feng, Chongrui Ye, Tianyang Luo +8

Large language model (LLM) agents have shown strong capabilities in reasoning, tool use, and multi-step interaction, but they often solve tasks from scratch and fail to reuse succe…

cs.CL2026

ElasticMem: Latent Memory as a Learnable Resource for LLM Agents

Tao Feng, Chongrui Ye, Tianyang Luo +5

Long-term memory is essential for LLM agents to reason coherently across extended interactions, personalize responses, and reuse past experience. However, existing memory-augmented…

cs.CL2026

Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory

Haozhen Zhang, Haodong Yue, Tao Feng +8

Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offline, query-agnostic memory const…

cs.NI2026

RouteProfile: Graph-Based Profiling for Cold-Start LLM Routing

Jingjun Xu, Hongji Pu, Tao Feng +3

LLM routing is increasingly important for selecting suitable models under diverse user needs and deployment constraints, but its practical effectiveness depends on continual adapta…