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Multimodal agents (MMAs) sustain interaction through reasoning, memory, tools, and feedback, most visibly as computer...
Quantitative research is an iterative loop: a researcher proposes a market hypothesis, implements it as an executable...
Consensus is a fundamental problem in distributed computing and at the core of state machine replication (SMR). Despi...
Through a tangle of real-world interactions, from synthetic training pipelines to data shared on the open web, fronti...
Existing world models typically perceive a scene through current visual frame or a narrow history window. However, th...
Existing sequential recommenders usually allocate a fixed computational budget to every item in a user's interaction ...
We present Qwen-Audio-3.1-ASR, a family of audio-language models that builds upon its predecesor Qwen-Audio-3.0-ASR w...
Autonomous agents can increasingly propose ideas, modify code, and run experiments, creating an opportunity to accele...
Agent learning is shifting from learning from human data toward learning through interaction with the world. However,...
Language-model agents that run long tasks often redo work they have already done: they re-issue a tool call they made...
Using an LLM to generate training data for another is among the most general ways to train one, and it remains common...
Spatial reasoning requires more than access to geometric tools: a reasoner must decide when direct observation is suf...