FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention
Long-context training of large language and multimodal models couples structured attention masks (document, prefix-LM...
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Long-context training of large language and multimodal models couples structured attention masks (document, prefix-LM...
Automatic speech recognition produces words but drops the non-verbal content of a recording: the breaths, coughs, sig...
The design of attention mechanisms in long-context large language models faces an ``impossible triangle'' among KV ca...
Simulated environments enable scalable training data generation for embodied agents, but more data does not necessari...
Game-theoretic benchmarks claim that large language model (LLM) strategic decision-making varies across game types, i...
Monocular world-space human recovery methods excel on current benchmarks, but these rarely include fast camera motion...
Embodied visual tracking requires a robot to identify a designated target from visual observations and control its ow...
Recent work has explored visual reasoning through image generation, where models solve visual-reasoning problems by d...
Vision-language models (VLMs) are increasingly deployed in multi-agent systems to automate complex computer-use workf...
Professional agents increasingly work through command-line interfaces and multiple tools over shared workspaces conta...
Language-model agents sometimes act beyond their authorization and then misreport what they did. On CAPE-Bench, match...
Linear attention promises the efficiency needed for long-context language modelling, yet its fixed-size recurrent sta...