most citedLarge Action Models: From Inception to Implementation

2 citations · 2 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CL2026

GraphForge: Training Working Agents with Graph-Anchored Workspace Synthesis

Qisheng Su, Hanchen Wang, Guanru Zhu +11

Working agents need to read diverse files, coordinate tools, and produce deliverables. Training such agents requires tasks built on many real files with verifiable results, but few…

cs.AI2026

Atria Dawn: The Dawn of Agentic Superintelligence

Honglin Guo, Tao Gui, Yicheng Chen +139

As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human researchers. We introduce Atria Dawn…

cs.AI2026

FACET: Preserving Source Intent and Executable State in Terminal Task Synthesis

Kou Shi, Zun Wang, Qisheng Su +10

Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples an instruction, an initialize…

cs.LG2026

Intern-S2-Preview: Scientific Agentic Foundation Model

Lei Bai, Jiaqi Cao, Chiyu Chen +121

Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…

cs.CV2026

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

Zhen Fang, Yu Zeng, Wenxuan Huang +17

We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense spatiotemporal grounding couple…

cs.CL2026

ACC: Compiling Agent Trajectories for Long-Context Training

Qisheng Su, Zhen Fang, Shiting Huang +8

Recent development of agents has renewed demand for long-context reasoning capacity of LLMs. However, training LLMs for this capacity requires costly long-document curation or heur…

cs.SE2026

SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering

Qingnan Ren, Shun Zou, Shiting Huang +11

As autonomous coding agents become capable of handling increasingly long-horizon tasks, they have gradually demonstrated the potential to complete end-to-end software development.…

cs.AI2026

SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents

Ziao Zhang, Kou Shi, Shiting Huang +13

As the capability frontier of autonomous agents continues to expand, they are increasingly able to complete specialized tasks through plug-and-play external skills. Yet current ben…

cs.PF2026

Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated Reasoning

Qisheng Su, Shiting Huang, Zhen Fang +3

In real-world Tool-Integrated Reasoning (TIR) scenarios, where LLMs interleave reasoning with external tool calls, a major source of inefficiency is that the toolcalls create pause…

cs.LG2026

Internalizing Meta-Experience into Memory for Guided Reinforcement Learning in Large Language Models

Shiting Huang, Zecheng Li, Yu Zeng +7

Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective approach for enhancing the reasoning capabilities of Large Language Models (LLMs). Despite its eff…

cs.CL2025

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage

Guangwei Zhang, Qisheng Su, Jiateng Liu +4

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) but pose risks of inadvertently exposing copyrighted or proprietary data, especially when such da…

cs.AI2025★ 2 cited

Large Action Models: From Inception to Implementation

Lu Wang, Fangkai Yang, Chaoyun Zhang +15

As AI continues to advance, there is a growing demand for systems that go beyond language-based assistance and move toward intelligent agents capable of performing real-world actio…