1 citations · 1 across the 14 of their papers we have counts for
15 papers
Quasinormal frequencies and greybody factors for axial perturbations of dilaton-Euler-Heisenberg de Sitter black holes
Ming Zhang, Guo-Xin Chen, Xufen Zhang +4
We investigate the quasinormal modes (QNMs) and greybody factors of dilaton-Euler-Heisenberg (dEH) de Sitter (dS) black holes in string-inspired Euler-Heisenberg gravity. Since the…
CalibForge: Adversarial Solver Calibration for Scaling Learnable Terminal Tasks
Fanzhe Meng, Guoxin Chen, Jiale Zhao +6
Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable validation establishes feasib…
DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch
Jiale Zhao, Guoxin Chen, Fanzhe Meng +4
As the capabilities of LLM-based code agents continue to advance, their expected role is expanding beyond localized bug fixing in existing codebases toward architecting and impleme…
Quasinormal modes and greybody factors of magnetically charged de Sitter black holes probed by massless external fields in Einstein Euler Heisenberg gravity
Ming Zhang, Guo-Xin Chen, Lei Zhang +3
This paper investigates the perturbation dynamics of massless scalar and electromagnetic fields on magnetically charged de Sitter (dS) black holes within the framework of string-in…
BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing?
Guoxin Chen, Fanzhe Meng, Jiale Zhao +12
Current code-agent benchmarks primarily evaluate localized issue resolution within a single target repository, leaving under-tested many software engineering tasks that require ext…
SWE-Master: Unleashing the Potential of Software Engineering Agents via Post-Training
Huatong Song, Lisheng Huang, Shuang Sun +11
In this technical report, we present SWE-Master, an open-source and fully reproducible post-training framework for building effective software engineering agents. SWE-Master system…
Computer Environments Elicit General Agentic Intelligence in LLMs
Daixuan Cheng, Shaohan Huang, Yuxian Gu +6
Agentic intelligence in large language models (LLMs) requires not only model intrinsic capabilities but also interactions with external environments. Equipping LLMs with computers…
IterResearch: Rethinking Long-Horizon Agents with Interaction Scaling
Guoxin Chen, Zile Qiao, Xuanzhong Chen +13
Recent advances in deep-research agents have shown promise for autonomous knowledge construction through dynamic reasoning over external sources. However, existing approaches rely…
AgentFrontier: Expanding the Capability Frontier of LLM Agents with ZPD-Guided Data Synthesis
Xuanzhong Chen, Zile Qiao, Guoxin Chen +7
Training large language model agents on tasks at the frontier of their capabilities is key to unlocking advanced reasoning. We introduce a data synthesis approach inspired by the e…
Tongyi DeepResearch Technical Report
Tongyi DeepResearch Team, Baixuan Li, Bo Zhang +54
We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking research tasks. To incentivize autonomous…
ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization
Guoxin Chen, Jing Wu, Xinjie Chen +6
Autoformalization, which translates natural language mathematics into machine-verifiable formal statements, is critical for using formal mathematical reasoning to solve math proble…
DecoupleSearch: Decouple Planning and Search via Hierarchical Reward Modeling
Hao Sun, Zile Qiao, Bo Wang +6
Retrieval-Augmented Generation (RAG) systems have emerged as a pivotal methodology for enhancing Large Language Models (LLMs) through the dynamic integration of external knowledge.…
MARS: Co-evolving Dual-System Deep Research via Multi-Agent Reinforcement Learning
Guoxin Chen, Zile Qiao, Wenqing Wang +10
Large Reasoning Models (LRMs) face two fundamental limitations: excessive token consumption when overanalyzing simple information processing tasks, and inability to access up-to-da…
WebResearcher: Unleashing unbounded reasoning capability in Long-Horizon Agents
Zile Qiao, Guoxin Chen, Xuanzhong Chen +13
Recent advances in deep-research systems have demonstrated the potential for AI agents to autonomously discover and synthesize knowledge from external sources. In this paper, we in…
Table-Critic: A Multi-Agent Framework for Collaborative Criticism and Refinement in Table Reasoning
Peiying Yu, Guoxin Chen, Jingjing Wang
Despite the remarkable capabilities of large language models (LLMs) in various reasoning tasks, they still struggle with table reasoning tasks, particularly in maintaining consiste…