2 citations · 5 across the 15 of their papers we have counts for
15 papers
ComBodied Agents: a New Paradigm of Human-Centric Agentic AI
Qianggang Ding, Xingyao Wang, Rui Feng +19
After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither explains whether the person fo…
Enhancing Software Engineering Through Closed-Loop Memory Optimization
Xuehang Guo, Zora Zhiruo Wang, Qingyun Wang +3
Large language models (LLMs) have enabled powerful software engineering (SE) agents capable of navigating complex codebases and resolving real-world issues. However, these agents r…
BAGEN: Are LLM Agents Budget-Aware?
Yuxiang Lin, Zihan Wang, Mengyang Liu +9
While agents are increasingly spending more resources, today agent cost is mostly measured only after execution. A Budget-Aware Agent (BAGEN) should treat budget as an active contr…
How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks
Longju Bai, Zhemin Huang, Xingyao Wang +5
The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that require a significant amount of t…
A Rubric-Supervised Critic from Sparse Real-World Outcomes
Xingyao Wang, Valerie Chen, Heng Ji +1
Academic benchmarks for coding agents tend to reward autonomous task completion, measured by verifiable rewards such as unit-test success. In contrast, real-world coding agents ope…
SWE-Milestone: Evaluating AI Agents on Continuous Software Evolution
Gangda Deng, Zhaoling Chen, Zhongming Yu +11
Real-world software must continuously evolve to meet ever-changing and open-ended requirements. AI agents, increasingly deployed as long-running systems, are now entrusted to drive…
The OpenHands Software Agent SDK: A Composable and Extensible Foundation for Production Agents
Xingyao Wang, Simon Rosenberg, Juan Michelini +8
Agents are now used widely in the process of software development, but building production-ready software engineering agents is a complex task. Deploying software agents effectivel…
Training Proactive and Personalized LLM Agents
Weiwei Sun, Xuhui Zhou, Weihua Du +5
Despite rapid progress, current AI agents are primarily optimized for isolated task completion. We argue for a paradigm shift toward training agents as collaborators that communica…
The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution
Junlong Li, Wenshuo Zhao, Jian Zhao +18
Real-world language agents must handle complex, multi-step workflows across diverse Apps. For instance, an agent may manage emails by coordinating with calendars and file systems,…
Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents
Yueqi Song, Ketan Ramaneti, Zaid Sheikh +18
Public research results on large-scale supervised finetuning of AI agents remain relatively rare, since the collection of agent training data presents unique challenges. In this wo…
TOM-SWE: User Mental Modeling For Software Engineering Agents
Xuhui Zhou, Valerie Chen, Zora Zhiruo Wang +3
Recent advances in coding agents have made them capable of planning, editing, running, and testing complex code bases. Despite their growing ability in coding tasks, these systems…
How can we assess human-agent interactions? Case studies in software agent design
Valerie Chen, Rohit Malhotra, Xingyao Wang +7
While benchmarks measure the accuracy of LLM-powered agents, they mostly assume full automation, failing to represent the collaborative nature of real-world use cases. In this pape…
Devstral: Fine-tuning Language Models for Coding Agent Applications
Abhinav Rastogi, Adam Yang, Albert Q. Jiang +100
We introduce Devstral-Small, a lightweight open source model for code agents with the best performance among models below 100B size. In this technical report, we give an overview o…
Coding Agents with Multimodal Browsing are Generalist Problem Solvers
Aditya Bharat Soni, Boxuan Li, Xingyao Wang +2
Modern human labor is characterized by specialization; we train for years and develop particular tools that allow us to perform well across a variety of tasks. In addition, AI agen…
The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks
Alejandro Cuadron, Dacheng Li, Wenjie Ma +13
Large Reasoning Models (LRMs) represent a breakthrough in AI problem-solving capabilities, but their effectiveness in interactive environments can be limited. This paper introduces…