9 citations · 21 across the 10 of their papers we have counts for
10 papers
Efficient Test-Time Adaptation through Human-AI Interaction
Zora Zhiruo Wang, Apurva Gandhi, Rulin Shao +22
AI agents are trained on population-scale data to encode broad capabilities spanning those of many practitioners. Yet the artifacts they produce rarely meet the personal bar profes…
Humans are Missing from AI Coding Agent Research
Zora Z. Wang, John Yang, Kilian Lieret +10
Recent progress in AI coding agent research has led to rapid improvements in agents' ability to autonomously perform complex software engineering tasks, from editing large codebase…
How Well Does Agent Development Reflect Real-World Work?
Zora Zhiruo Wang, Sanidhya Vijayvargiya, Aspen Chen +7
AI agents are increasingly developed and evaluated on benchmarks relevant to human work, yet it remains unclear how representative these benchmarking efforts are of the labor marke…
Hybrid-Gym: Training Coding Agents to Generalize Across Tasks
Yiqing Xie, Emmy Liu, Gaokai Zhang +7
When assessing the quality of coding agents, predominant benchmarks focus on solving single issues on GitHub, such as SWE-Bench. In contrast, in real use, these agents solve more v…
How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations
Zora Zhiruo Wang, Yijia Shao, Omar Shaikh +3
AI agents are continually optimized for tasks related to human work, such as software engineering and professional writing, signaling a pressing trend with significant impacts on t…
Inducing Programmatic Skills for Agentic Tasks
Zora Zhiruo Wang, Apurva Gandhi, Graham Neubig +1
To succeed in common digital tasks such as web navigation, agents must carry out a variety of specialized tasks such as searching for products or planning a travel route. To tackle…
Agent Workflow Memory
Zora Zhiruo Wang, Jiayuan Mao, Daniel Fried +1
Despite the potential of language model-based agents to solve real-world tasks such as web navigation, current methods still struggle with long-horizon tasks with complex action tr…
What Are Tools Anyway? A Survey from the Language Model Perspective
Zhiruo Wang, Zhoujun Cheng, Hao Zhu +2
Language models (LMs) are powerful yet mostly for text generation tasks. Tools have substantially enhanced their performance for tasks that require complex skills. However, many wo…
TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Tasks
Zhiruo Wang, Daniel Fried, Graham Neubig
Language models (LMs) can solve tasks such as answering questions about tables or images by writing programs. However, using primitive functions often leads to verbose and error-pr…
API-Assisted Code Generation for Question Answering on Varied Table Structures
Yihan Cao, Shuyi Chen, Ryan Liu +2
A persistent challenge to table question answering (TableQA) by generating executable programs has been adapting to varied table structures, typically requiring domain-specific log…