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

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7 papers

cs.CL2026

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

Junlin Yang, Che Jiang, Yu Fu +21

The paper presents Frontis-MA1, a 35‑billion‑parameter model trained as a meta‑evolution agent for machine learning engineering, using a new OpenMLE stack that combines operator le…

cs.CV2026

DepthART: Scaling Foundation Monocular Depth to Tiny Models

Feng Xue, Wu Chen, Mingshuai Zhao +7

Recent geometric foundation models (e.g., Metric3D, Depth Anything and UniDepth) have substantially improved monocular depth estimation (MDE) in both cross-scene generalization and…

cs.CL2026

EnterpriseClawBench: Benchmarking Agents from Real Workplace Sessions

Jincheng Zhong, Weizhi Wang, Che Jiang +5

Enterprise agents increasingly operate inside workspaces: they read heterogeneous files, invoke tools, and deliver business artifacts. We introduce EnterpriseClawBench, an enterpri…

cs.CV2026

Think Less, Act Early: Reinforced Latent Reasoning with Early Exit in Vision-Language-Action Models

Dianqiao Lei, Lianlei Shan

Existing Vision-Language-Action (VLA) models predominantly rely on explicit Chain-of-Thought (CoT) reasoning to bridge perception and action. While effective, this paradigm suffers…

cs.CV2026

The 1st PortraitCraft Challenge: A CVPR 2026 Workshop Competition on Portrait Composition Understanding and Generation

Zijie Lou, Youyun Tang, Xiaochao Qu +40

This paper presents an overview of the inaugural PortraitCraft Challenge, held as one of the official competitions at CVPR 2026. The challenge focuses on portrait composition under…

cs.AI2026

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization

Yizhe Chi, Deyao Hong, Dapeng Jiang +18

Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often neglect the value of real-world…