activity
20242026
most citedStyleShot: A Snapshot on Any Style

2 citations · 4 across the 10 of their papers we have counts for

collaborators

13 papers

cs.LG2026

OS-Helix: Unifying GUI Interaction and Code Execution in Native Computer-Using Agents

Bowen Yang, Kaiming Jin, Zichen Ding +8

Real desktop automation is neither purely visual nor purely programmatic. Agents must understand user-facing interfaces while efficiently manipulating files, scripts, and system st…

cs.CV2026

MegaStyle++: Scaling Image Style Space through Hierarchical Style Definition

Junyao Gao, Sibo Liu, Jiaxing Li +4

Image style is a highly abstract, human-constructed concept shaped by a range of visual factors and intrinsically entangled with content, yet a unified and explicit definition of i…

cs.AI2026

Is Next-Chunk Reasoning RL Really Better than SFT? Revisiting Training Strategies under no-CoT Data

Yinhao Tang, Youqing Fang, Yanan Sun +8

Recent work proposes next-chunk reasoning RL for leveraging no-CoT data---corpora such as worked solutions and textbook derivations that contain reasoning-rich content but lack exp…

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.AI2026

SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration

Yinhao Tang, Youqing Fang, Yanan Sun +6

Scientific research involves complex information-seeking and reasoning workflows across heterogeneous sources. However, existing benchmarks primarily emphasize general-domain retri…

cs.CV2026

SyncCache: Exploiting Asymmetric Dynamics for Fast Audio-Driven Portrait Animation

Juncheng Ma, Yuxuan Du, Yanan Sun +8

Diffusion Transformers (DiTs) have significantly advanced audio-driven portrait animation, but their high computational cost leads to substantial inference latency. Although traini…

cs.HC2026

MindCopilot: Towards Formalizing and Evaluating Granular Human-LLM Co-Writing

Youqing Fang, Yinhao Tang, Yanan Sun +8

Recent writing assistants are increasingly shifting from passive, prompt-driven interaction to proactive, suggestion-based completion, which integrates localized continuations into…

cs.AI2026

TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration

Zerun Ma, Guoqiang Wang, Xinchen Xie +7

While Large Language Models (LLMs) have empowered AI research agents to perform isolated scientific tasks, automating complex, real-world workflows, such as LLM training, remains a…

cs.CV2026★ 1 cited

MegaStyle: Constructing Diverse and Scalable Style Dataset via Consistent Text-to-Image Style Mapping

Junyao Gao, Sibo Liu, Jiaxing Li +6

In this paper, we introduce MegaStyle, a novel and scalable data curation pipeline that constructs an intra-style consistent, inter-style diverse and high-quality style dataset. We…

cs.SE2025

Human-Agent Collaborative Paper-to-Page Crafting

Qianli Ma, Siyu Wang, Yilin Chen +7

In the quest for scientific progress, communicating research is as vital as the discovery itself. Yet, researchers are often sidetracked by the manual, repetitive chore of building…

cs.CV2025★ 1 cited

CharacterShot: Controllable and Consistent 4D Character Animation

Junyao Gao, Jiaxing Li, Wenran Liu +5

In this paper, we propose \textbf{CharacterShot}, a controllable and consistent 4D character animation framework that enables any individual designer to create dynamic 3D character…

cs.AI2025

LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?

Kexian Tang, Junyao Gao, Yanhong Zeng +6

Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning across multiple sequential step…

cs.CV2024★ 2 cited

StyleShot: A Snapshot on Any Style

Junyao Gao, Yanchen Liu, Yanan Sun +4

In this paper, we show that, a good style representation is crucial and sufficient for generalized style transfer without test-time tuning. We achieve this through constructing a s…