arXiv AI
Jul 7
Wan-Streamer v0.2: Higher Resolution, Same Latency
arXiv:2607. 04443v1 Announce Type: cross Abstract: We present Wan-Streamer v0.
Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models
arXiv:2606. 25041v2 Announce Type: replace-cross Abstract: 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.
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arXiv AI
Jun 8
Don't Pause: Streaming Video-Language Synchrony for Online Video Understanding
arXiv:2606. 06991v1 Announce Type: cross Abstract: Online Video Large Language Models (Video-LLMs) have advanced toward seamless human-AI interaction through frame-by-frame processing and proactive responding.
arXiv AI
Aug 11
Aero Realtime: Fully Aligned Input-Output Streams for Low-Latency Streaming Multimodal Generation
arXiv:2608. 08469v1 Announce Type: new Abstract: Existing streaming multimodal models process observations incrementally but still follow a turn-based prefill-then-decode pattern, making them non-duplex: new observations cannot naturally enter an active generation stream.
arXiv AI
Jun 4
Audio Interaction Model
arXiv:2606. 05121v1 Announce Type: cross Abstract: Audio is an inherently interactive modality, yet today's Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only a single task such as streaming ASR or voice chatting.
Hugging Face Trending Papers
Aug 6
Vorch-Streamer: Extending Human Audio-Visual Generation to Real-Time Long-Form Streaming
Real-time long-form avatar audio--video generation requires causal, continuous synthesis while maintaining audiovisual synchronization and visual consistency. Adapting a pretrained bidirectional model to this setting presents two key dilemmas.
arXiv AI
Aug 12
Ex-Omni-2D: Expressive Omni-Modal Dialogue Models with Native Visual Presence
arXiv:2608. 10720v1 Announce Type: new Abstract: Omni-modal dialogue models can understand multimodal inputs and synthesize spoken replies, yet their responses remain visually disembodied.
arXiv AI
Jun 9
Liberating LLM Capabilities in Full-Duplex Speech Models
arXiv:2606. 07547v1 Announce Type: cross Abstract: Speech-based large language models are typically constrained to spoken replies, which limits their user-facing outputs to what can be verbalized and suppresses text-native capabilities such as code generation, structured analysis, and multi-step reasoning in realtime interaction, for tasks that require persistent, structured, and inspectable intermediate outputs.
arXiv AI
Jun 30
FacePlex: Full-Duplex Joint Speech-Facial Motion Generation for Conversational Avatars
arXiv:2606. 30145v1 Announce Type: new Abstract: Natural face-to-face conversation requires real-time speech generation together with synchronized facial motion.
Hugging Face Trending Papers
Jun 29
FacePlex: Full-Duplex Joint Speech-Facial Motion Generation for Conversational Avatars
Natural face-to-face conversation requires real-time speech generation together with synchronized facial motion. Existing systems only partially address this problem: speech-only full-duplex models can generate speech in real time but do not produce facial motion, while audio-driven facial motion models animate a face from already available audio rather than jointly generating speech and motion online.
arXiv AI
Jun 9
MOSS-Video-Preview: Toward Real-Time Video Understanding via Cross-Attention
arXiv:2606. 07639v1 Announce Type: cross Abstract: Video understanding is shifting from the offline paradigm -- taking a fully recorded video as input and producing a single answer after it ends -- toward real-time interaction, in which the model perceives new frames while still replying, revises its answer as new evidence appears, and remains silent when there is nothing to say.
arXiv AI
Jun 10
From Senses to Decisions: The Information Flow of Auditory and Visual Perception in Multimodal LLMs
arXiv:2606. 10147v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) can listen and see, but how do audio and visual signals actually travel through the network to shape an answer?
arXiv AI
Jul 13
M4V: Multimodal Mamba for Efficient Text-to-Video Generation
arXiv:2506. 10915v2 Announce Type: replace-cross Abstract: Text-to-video generation has significantly enriched content creation and holds the potential to evolve into powerful world simulators.