1 citations · 2 across the 11 of their papers we have counts for
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Tandem: Serving Hybrid Linear-Attention GUI Agents on Mobile NPUs
Zhuomin Chen, Jingchao Ni, Xu Zheng +4
Smartphone GUI agents complete tasks in mobile apps by repeatedly reading the screen and asking a model for the next action. Mobile neural processing units (NPUs) enable local exec…
SpecForge: Recursive Self-Improvement for Coding Agents via Behavioral Specifications
Yutong Cheng, Haifeng Chen, Peng Gao +1
Coding agents based on frozen language models can improve their performance by refining the external context they rely on, without updating model weights. We study recursive self-i…
WorkflowOps: Learning Agent Collaboration Priors for Multi-Agent Workflow Orchestration
Qi Cheng, Shengyu Chen, Wei Cheng +4
Multi-agent systems are increasingly deployed for complex knowledge work, yet their orchestration layers remain largely memoryless: each new task is decomposed, assigned, and execu…
RA-MoWE: Workflow-Affinity Embeddings for Query Clustering and Agentic Workflow Generation
Qi Cheng, Shengyu Chen, Wei Cheng +4
Agentic workflows enable large language models (LLMs) to solve complex tasks by coordinating reasoning, tool use, and verification. However, a workflow optimized for an entire task…
OOPMAS: Object-Oriented Multi-Agent Systems for Query-Level Workflow Generation
Qi Cheng, Shengyu Chen, Wei Cheng +4
Multi-agent systems (MAS) powered by large language models have shown strong performance across code generation, mathematical reasoning, and question answering. However, existing m…
ST-Bench: A Spatial-Temporal Benchmark for Multi-Agent System Generation on Scientific Research Tasks
Qi Cheng, Rongchao Dong, Shengyu Chen +8
The rapid progress of LLM-based multi-agent systems (MAS) has shown that they largely outperform single agents on coding, math, and QA tasks, where executable tests provide a binar…
Do Time-Series QA Systems Read the Time Series? Evidence Use and Reasoning Reliability
Zhuomin Chen, Jingchao Ni, Xu Zheng +4
In recent years, time-series question answering (QA) systems have made significant progress. However, generating a correct answer does not show whether retaining the supplied numer…
Pay for the Fault, Not the Flow: Label-Free In-Flow Multi-Agent Workflow Optimization
Xuehang Guo, Haoyu Wang, Shengyu Chen +4
Large language models (LLMs) increasingly construct multi-agent workflows that decompose a complex task and assign specialist agents from a pool. However, building such a workflow…
Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems
Xu Zheng, Zhuomin Chen, Chaohao Lin +4
Large Language Model~(LLM)-based agents have demonstrated exceptional performance across a wide range of complex interactive tasks. However, they often struggle with long-horizon i…
Bridging Inference-Time Scaling and Episodic Memory with Action-Centric Graphs
Xu Zheng, Chaohao Lin, Zhuomin Chen +4
Recent advancements in inference-time scaling have significantly unlocked the complex reasoning capabilities of Large Language Models~(LLMs). However, for agents, these approaches…
DecoSearch: Complexity-Aware Routing and Plan-Level Repair for Text-to-SQL
Esteban Schafir, Xu Zheng, Hojat Allah Salehi +4
Large Language Models (LLMs) have demonstrated remarkable capabilities in translating natural language to SQL, yet existing methods still falter on complex queries requiring multi-…