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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.CV2026

AutoDesign: Meta-Harness Optimization for Long-Horizon Agentic Design

Yaxin Luo, Haobin Jiang, Jialv Zou +11

Transforming multimodal sources into condensed and structured media outputs can be fundamentally conceptualized as a long-horizon agentic process centered on a model-harness system…

cs.CV2026

VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System

Haodong Li, Tianfei Ren, Xiaoxiao Ma +25

The paper presents VideoCoCo, a system that generates physically consistent videos by having a coding agent produce executable Blender code that defines the scene and its dynamics,…

cs.CV2026

LongCat-Next: Lexicalizing Modalities as Discrete Tokens

Meituan LongCat Team, Bin Xiao, Chao Wang +86

The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…

cs.CV2026

Senna-2: Aligning VLM and End-to-End Driving Policy for Consistent Decision Making and Planning

Yuehao Song, Shaoyu Chen, Hao Gao +8

Vision-language models (VLMs) enhance the planning capability of end-to-end (E2E) driving policy by leveraging high-level semantic reasoning. However, existing approaches often ove…

cs.CV2025

DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving

Jialv Zou, Shaoyu Chen, Bencheng Liao +6

Generative diffusion models for end-to-end autonomous driving often suffer from mode collapse, tending to generate conservative and homogeneous behaviors. While DiffusionDrive empl…

cs.CV2025

ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Driving

Zhiyu Zheng, Shaoyu Chen, Haoran Yin +5

End-to-end autonomous driving (E2EAD) systems, which learn to predict future trajectories directly from sensor data, are fundamentally challenged by the inherent spatio-temporal im…