16 citations · 33 across the 23 of their papers we have counts for
25 papers
Foundation Protocol: A Coordination Layer for Agentic Society
Bang Liu, Yongfeng Gu, Jiayi Zhang +26
Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly interact with one another. A…
Scalable Environments Drive Generalizable Agents
Jiayi Zhang, Fanqi Kong, Guibin Zhang +7
Generalizable agents should adapt to diverse tasks and unseen environments beyond their training distribution. This position paper argues that such generalization requires environm…
Harnessing Agentic Evolution
Jiayi Zhang, Yongfeng Gu, Jianhao Ruan +10
Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, evaluating them, and using fe…
Co-Evolution of Policy and Internal Reward for Language Agents
Xinyu Wang, Hanwei Wu, Jingwei Song +8
Large language model (LLM) agents learn by interacting with environments, but long-horizon training remains fundamentally bottlenecked by sparse and delayed rewards. Existing metho…
AnnoRetrieve: Efficient Structured Retrieval for Unstructured Document Analysis
Teng Lin, Yuyu Luo, Nan Tang
Unstructured documents dominate enterprise and web data, but their lack of explicit organization hinders precise information retrieval. Current mainstream retrieval methods, especi…
AutoWebWorld: Synthesizing Infinite Verifiable Web Environments via Finite State Machines
Yifan Wu, Yiran Peng, Yiyu Chen +12
The performance of autonomous Web GUI agents heavily relies on the quality and quantity of their training data. However, a fundamental bottleneck persists: collecting interaction t…
AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration
Jianhao Ruan, Zhihao Xu, Yiran Peng +9
Language agents have shown strong promise for task automation. Realizing this promise for increasingly complex, long-horizon tasks has driven the rise of a sub-agent-as-tools parad…
Towards Agentic Intelligence for Materials Science
Huan Zhang, Yizhan Li, Wenhao Huang +18
The convergence of artificial intelligence and materials science presents a transformative opportunity, but achieving true acceleration in discovery requires moving beyond task-iso…
Enhancing Table Reasoning with Deterministic Table-State Rewards
Tung Sum Thomas Kwok, Xinyu Wang, Hengzhi He +9
Large Language Models (LLMs) struggle with multi-step reasoning over structured tables. The primary reason is the lack of explicit supervision for intermediate reasoning states. Ex…
From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence
Jian Yang, Xianglong Liu, Weifeng Lv +68
Large language models (LLMs) have fundamentally transformed automated software development by enabling direct translation of natural language descriptions into functional code, dri…
AutoEnv: Automated Environments for Measuring Cross-Environment Agent Learning
Jiayi Zhang, Yiran Peng, Fanqi Kong +12
Humans naturally adapt to diverse environments by learning underlying rules across worlds with different dynamics, observations, and reward structures. In contrast, existing agents…
InteractComp: Evaluating Search Agents With Ambiguous Queries
Mingyi Deng, Lijun Huang, Yani Fan +23
Language agents have demonstrated remarkable potential in web search and information retrieval. However, many search-agent benchmarks assume that user queries are complete and unam…
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
Yizhang Zhu, Liangwei Wang, Chenyu Yang +22
The rapid advancement of large language models (LLMs) has spurred the emergence of data agents, autonomous systems designed to orchestrate Data + AI ecosystems for tackling complex…
ReCode: Unify Plan and Action for Universal Granularity Control
Zhaoyang Yu, Jiayi Zhang, Huixue Su +9
Real-world tasks require decisions at varying granularities, and humans excel at this by leveraging a unified cognitive representation where planning is fundamentally understood as…
VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations
Yupeng Xie, Zhiyang Zhang, Yifan Wu +8
Visualization, a domain-specific yet widely used form of imagery, is an effective way to turn complex datasets into intuitive insights, and its value depends on whether data are fa…
DeepEye-SQL: A Software-Engineering-Inspired Text-to-SQL Framework
Boyan Li, Chong Chen, Zhujun Xue +2
Large language models (LLMs) have advanced Text-to-SQL, yet existing solutions still fall short of system-level reliability. The limitation is not merely in individual modules -- e…
DeepVIS: Bridging Natural Language and Data Visualization Through Step-wise Reasoning
Zhihao Shuai, Boyan Li, Siyu Yan +2
Although data visualization is powerful for revealing patterns and communicating insights, creating effective visualizations requires familiarity with authoring tools and often dis…
RobustFlow: Towards Robust Agentic Workflow Generation
Shengxiang Xu, Jiayi Zhang, Shimin Di +5
The automated generation of agentic workflows is a promising frontier for enabling large language models (LLMs) to solve complex tasks. However, the empirical study reveals that ex…
Beyond Structure: Invariant Crystal Property Prediction with Pseudo-Particle Ray Diffraction
Bin Cao, Yang Liu, Longhan Zhang +6
Crystal property prediction, governed by quantum mechanical principles, is computationally prohibitive to solve exactly for large many-body systems using traditional density functi…
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Bang Liu, Xinfeng Li, Jiayi Zhang +45
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…
Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search
Boyan Li, Jiayi Zhang, Ju Fan +4
Text-to-SQL, which enables natural language interaction with databases, serves as a pivotal method across diverse industries. With new, more powerful large language models (LLMs) e…
Atom of Thoughts for Markov LLM Test-Time Scaling
Fengwei Teng, Quan Shi, Zhaoyang Yu +4
Large Language Models (LLMs) have achieved significant performance gains through test-time scaling methods. However, existing approaches often incur redundant computations due to t…
Self-Supervised Prompt Optimization
Jinyu Xiang, Jiayi Zhang, Zhaoyang Yu +8
Well-designed prompts are crucial for enhancing Large language models' (LLMs) reasoning capabilities while aligning their outputs with task requirements across diverse domains. How…
AFlow: Automating Agentic Workflow Generation
Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu +11
Large language models (LLMs) have demonstrated remarkable potential in solving complex tasks across diverse domains, typically by employing agentic workflows that follow detailed i…