6 papers
Not Worth Another Token: Marginal Value Estimation for Efficient Deep Research Agents
Harshitha Kolukuluru, Reshma Ashok, Kirat Arora +7
Long-horizon research agents solve open-ended tasks through iterative retrieval, aggregation, and synthesis, but context grows rapidly while the marginal value of additional eviden…
Cost-Aware Optimization for Agentic Query Execution
Lunyiu Nie, Yilin Xia, Yiren Liu +2
Classical query optimization searches over algebraically equivalent plans that differ only in cost. This assumption breaks once LLM-backed operators enter the picture: their placem…
When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding
Xu Yang, Lunyiu Nie, Ethan Chandra +3
Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. However, adding agents in prac…
Efficient Tree-Structured Deep Research with Adaptive Resource Allocation
Lunyiu Nie, Nedim Lipka, Ryan A. Rossi +1
Deep research agents, which synthesize information across diverse sources, are significantly constrained by the sequential nature of reasoning. This bottleneck results in high late…
Resource-efficient Inference with Foundation Model Programs
Lunyiu Nie, Zhimin Ding, Kevin Yu +3
The inference-time resource costs of large language and vision models present a growing challenge in production deployments. We propose the use of foundation model programs, i.e.,…
Online Cascade Learning for Efficient Inference over Streams
Lunyiu Nie, Zhimin Ding, Erdong Hu +2
Large Language Models (LLMs) have a natural role in answering complex queries about data streams, but the high computational cost of LLM inference makes them infeasible in many suc…