activity
20232025
most citedAutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

178 citations · 181 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute

Dujian Ding, Ankur Mallick, Shaokun Zhang +7

Large language models (LLMs) are powerful tools but are often expensive to deploy at scale. LLM query routing mitigates this by dynamically assigning queries to models of varying c…

cs.CL20251 cited

Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning

Shaokun Zhang, Yi Dong, Jieyu Zhang +6

Enabling large language models with external tools has become a pivotal strategy for extending their functionality beyond text space. To enhance LLMs' tool-calling abilities, previ…

cs.AI20241 cited

EcoAct: Economic Agent Determines When to Register What Action

Shaokun Zhang, Jieyu Zhang, Dujian Ding +7

Recent advancements have enabled Large Language Models (LLMs) to function as agents that can perform actions using external tools. This requires registering, i.e., integrating tool…

cs.AI2023178 cited

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Qingyun Wu, Gagan Bansal, Jieyu Zhang +11

AutoGen is an open-source framework that allows developers to build LLM applications via multiple agents that can converse with each other to accomplish tasks. AutoGen agents are c…

cs.LG20231 cited

HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shifts

Shaokun Zhang, Yiran Wu, Zhonghua Zheng +2

In this work, we propose a hyperparameter optimization method named \emph{HyperTime} to find hyperparameters robust to potential temporal distribution shifts in the unseen test dat…