multimodality

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#multimodality

We’re releasing Jev 1.14.0 along with experimental features for dreamers

Hacker News Top ↗ · 2026-10-14 Cached

TypeSafe 发布 Jev 1.14.0 模型更新,并通过 "danger zone" 实验性功能引入图像支持、新的 box 边界框类型以及更长的上下文长度,面向开发者与创意用户开放预览。

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#multimodality

@randall_balestr: Delighted to be speaking about our recent progress on JEPAs and on the need for more principled solutions that handle d…

X AI KOLs Following ↗ · 2026-10-01 Cached

Randal Balestrero announces his keynote talk at MICCAI-FOMO26 on recent progress in Joint-Embedding Predictive Architectures (JEPAs) and the need for more principled approaches to data imbalance, noise, multimodality, and reasoning.

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#multimodality

Understanding Multimodality in Generative Behavioral Cloning

Hugging Face Daily Papers ↗ · 2026-09-30 Cached

This paper formalizes multimodality in generative behavioral cloning and finds, through theory and extensive experiments on LIBERO, Meta-World, and synthetic benchmarks, that common simulation benchmarks are largely unimodal and that simple deterministic action transformers remain competitive with expressive generative policies such as diffusion, flow, and CVAE-based methods.

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#multimodality

LLMs are General Asynchronous Agents

Hugging Face Daily Papers ↗ · 2026-09-28 Cached

The paper proposes a general asynchronous LLM framework that lets users define inference coroutines with overlapping memory states, demonstrating that Qwen3.x models can handle streaming video, video games, and monitoring tasks asynchronously without task-specific training.

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#multimodality

Slow to See, Slow to Suppress: Understanding the Effects of Modality in Context-Memory Conflicts

arXiv cs.CL ↗ · 2026-09-02 Cached

The paper examines how vision-language models handle conflicts between in-context and parametric knowledge, revealing asymmetric biases where models favor in-context information for text entities but parametric information for image entities due to slower visual processing.

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#multimodality

Can Conversational Temporal Dynamics Improve Depression Detection in Dyads? A Preliminary Investigation in Multi-Modality Perspectives

arXiv cs.AI ↗ · 2026-07-07 Cached

This paper investigates the use of conversational temporal dynamics (turn-pair timing) as a lightweight modality for automatic depression detection from dyadic clinical interviews, showing that a compact 24-dimensional timing module achieves strong performance and complements standard acoustic and semantic features when fused.

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