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From the 1 of 10 linked papers with an AI index.

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10 papers

cs.CV2026

Video = World + Event Stream

Lianghua Huang, Zhi-Fan Wu, Yupeng Shi +24

The paper introduces Wan-Streamer v0.3, a model that treats video as a combination of a persistent world and a dynamic event stream, enabling real-time multimodal audio‑visual inte…

cs.CV2026

Wan-Streamer v0.2: Higher Resolution, Same Latency

Lianghua Huang, Zhi-Fan Wu, Yupeng Shi +23

We present Wan-Streamer v0.2, a latency-preserving upgrade of the native-streaming, end-to-end audio-visual interaction model. v0.2 keeps the v0.1 modeling formulation, but raises…

cs.CV2026

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

Lianghua Huang, Zhi-Fan Wu, Wei Wang +22

We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex audio-visual interaction. W…

cs.CV2026

Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety

Shikai Qiu, Xiaowen Xu, Benlei Cui +55

General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversarial nature of content and AI s…

cs.AI2026

Agent-as-a-Router: Agentic Model Routing for Coding Tasks

Pengfei Zhou, Zhiwei Tang, Yixing Ma +8

Real-world users typically have access to multiple Large Language Models (LLMs) from different providers, and these LLMs often excel at distinct domains, yet none dominate all. Con…

cs.LG2026

Discovering Millions of Interpretable Features with Sparse Autoencoders

XinYang He, Wei Wang, Bing Zhao +5

Sparse autoencoders (SAEs) have emerged as a powerful tool for decomposing superposed language model representations into sparse and interpretable features. However, training SAEs…