activity
20242026
collaborators

11 papers

cs.AI2026

Game-Creation-Agents: Autonomous Game Production

Tencent Multimodal RL Team, Xiangxin Zhou, Jiaqi Tang +15

Game-Creation-Agents (GCA) turns a natural-language request into a runnable Phaser 4 browser game. The pipeline first builds a multimodal game design document that couples mechanic…

cs.LG2026

Why Are GUI Agents Correct but Late? Decode on the Decision-Time Critical Path, Tested with Pre-Compiled Policy Trees

Zihan Dong, Rui Qian, Qishi Zhan +3

Computer-use agents often fail on transient GUI events because they produce the correct action only after the relevant window has already closed. We identify the main cause as expe…

cs.AI2026

Scaling GUI Agents with Visual State Transitions

Xiangyan Liu, Kaixin Li, Haonan Wang +6

We introduce State Transition Pretraining (STP) as a new scaling axis for GUI agents. During the STP stage, we continually pretrain a unified multimodal model on visual state trans…

cs.CV2026

JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents

Yunlong Lin, Zixu Lin, Zhaohu Xing +23

Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high-quality images, videos, aud…

cs.AI2026

From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms

Jinghao Luo, Yuchen Tian, Chuxue Cao +6

Large Language Model (LLM)-based agents have fundamentally reshaped artificial intelligence by integrating external tools and planning capabilities. While memory mechanisms have em…

cs.CL2025

MM-CRITIC: A Holistic Evaluation of Large Multimodal Models as Multimodal Critique

Gailun Zeng, Ziyang Luo, Hongzhan Lin +5

The ability of critique is vital for models to self-improve and serve as reliable AI assistants. While extensively studied in language-only settings, multimodal critique of Large M…

cs.CL2025

MemeArena: Automating Context-Aware Unbiased Evaluation of Harmfulness Understanding for Multimodal Large Language Models

Zixin Chen, Hongzhan Lin, Kaixin Li +3

The proliferation of memes on social media necessitates the capabilities of multimodal Large Language Models (mLLMs) to effectively understand multimodal harmfulness. Existing eval…

cs.DB2025

AmbiGraph-Eval: Can LLMs Effectively Handle Ambiguous Graph Queries?

Yuchen Tian, Kaixin Li, Hao Chen +5

Large Language Models (LLMs) have recently demonstrated strong capabilities in translating natural language into database queries, especially when dealing with complex graph-struct…

cs.CL2025

AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness

Zixin Chen, Hongzhan Lin, Kaixin Li +5

The proliferation of multimodal memes in the social media era demands that multimodal Large Language Models (mLLMs) effectively understand meme harmfulness. Existing benchmarks for…

cs.CV2025

ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use

Kaixin Li, Ziyang Meng, Hongzhan Lin +5

Recent advancements in Multi-modal Large Language Models (MLLMs) have led to significant progress in developing GUI agents for general tasks such as web browsing and mobile phone u…

cs.CL2024

Towards Better Text-to-Image Generation Alignment via Attention Modulation

Yihang Wu, Xiao Cao, Kaixin Li +4

In text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results. However, these models encounter challenges when processi…