Archived
2026-10-07WorldSonus: Bringing Sound to Worlds
Pengjun Fang, Jingyi Fa, Kam Man Wu, Jiaming Wang, Haoyuan Huang, Yaguang Wu, et al.
arXiv:2610.08760v1Today’s standout is WorldSonus, a system that gives world models something they’ve mostly been missing: sound. Most recent world models can generate convincing video, but they stay silent, which makes them less useful for interactive simulation, robotics, and embodied AI. WorldSonus tackles three hard problems at once: it has to generate audio in real time, respond to new sound instructions while a scene is already unfolding, and keep stereo sound aligned with the scene’s geometry and camera motion. The core idea is a streaming diffusion model that produces audio chunk by chunk, paired with an audio captioning and prompt scheduling scheme for mid-stream control, plus stereo supervision to preserve spatial realism. The result is a practical video-to-audio system that runs fast enough for live use and generalizes well beyond world-model settings. That matters because realistic simulated environments are not truly immersive, or fully useful for agents, until they can hear as well as see.
Also spotted that day
QF3: Fast Flow RL with Filtered Q-GradientsConformal Prediction Sets Quantify Information Gain: A Theoretical Perspective4D-HOF: Hand-Object Flow Matching for Feed-Forward 4D Interaction ReconstructionIdeaAnchor: Teaching LLMs to Turn Literature into Research IdeasDepthWorld: 3D World Model for Robot ManipulationSherpa: Teaching LLMs to Teach AdaptivelyAgent in a Bottle: Can LLM Agents Turn Their Capabilities Into Cheap, Scalable Artifacts?AdvSim2Real : Training Web Agents Against Adaptive Prompt Injection in a Web World ModelRapid Fredholm stabilization of the Kuramoto--Sivashinsky equation with unrestricted, spatially-varying anti-diffusionVeriFine: Scaling Verification for Self-Improvement in Embodied ReasoningNeural Petri flows for chemical reactionsThe Missing Minimal Pair: Stereotype Evaluation in LLMsLinear Bandits under Exact Sliding-Window ConstraintsReinforcement Learning with Conformal Action Sets: An Application to Sequential Recommendation
Previous daily papers
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