—The deep-learning scaling that drove the past decade of AI is colliding with hard limits in energy, data, robustness, and explainability, just as emerging applications demand the capabilities neural networks lack: reasoning, abstraction, and collaboration. The CoCoSys JUMP 2.0 center confronts this by co-designing cog...
Zi-Shen Wan, Yu Cao, S. K. Gupta et al.· IEEE Micro· 0 citations
This work focuses on semantic heterogeneity and studies how it should shape the management and evaluation of working memory in coding agents, finding that semantically different working-memory objects exhibit distinct retention and compression behavior.
Le Chen, Zi-Shen Wan, Bai-Xi Sun et al.· 1 citation
Dyserve compiles each workflow's per-node model and verifier choices in one integer linear program (ILP) over a heterogeneous backend pool, priced by skill-conditioned offline profiles that transfer across workflows.
Jiayi Qian, Zishen Wan, Hanchen Yang et al.· 0 citations
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