most citedFrom Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2025

How Far Are We from Genuinely Useful Deep Research Agents?

Dingling Zhang, He Zhu, Jincheng Ren +15

Deep Research Agents (DRAs) aim to automatically produce analyst-level reports through iterative information retrieval and synthesis. However, most existing DRAs were validated on…

cs.SE20251 cited

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…

cs.CL2025

AFM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning

Qianben Chen, Jingyi Cao, Jiayu Zhang +12

Large language models split into two families: reasoning-centric LLMs, which strengthen internal chain-of-thought reasoning but cannot invoke external tools, and agentic LLMs, whic…

cs.CL2025

ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems

Xin Gui, King Zhu, JinCheng Ren +17

In recent years, the research focus of large language models (LLMs) and agents has shifted increasingly from demonstrating novel capabilities to complex reasoning and tackling chal…

cs.AI2025

Flash-Searcher: Fast and Effective Web Agents via DAG-Based Parallel Execution

Tianrui Qin, Qianben Chen, Sinuo Wang +10

Large language models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks when equipped with external tools. However, current frameworks predominantly rely…

cs.AI2025

Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL

Weizhen Li, Jianbo Lin, Zhuosong Jiang +27

Recent advances in large language models (LLMs) and multi-agent systems have demonstrated remarkable capabilities in complex problem-solving tasks such as deep research, vibe codin…