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Questions about an agent's history often require aggregating events, which retrieval alone does not resolve. We combine source-preserving evidence access with executable aggregation. Trajectory Memory (TM) retains the original trajectory and constructs a source-addressable reading view at question time. TallyMem augmen...
We present OPENHARMONY BENCH, an app-level coding benchmark for evaluating LLM-based coding agents on OpenHarmony ArkTS applications. Unlike function-level benchmarks, it evaluates complete app-level changes: each task requires an agent to modify a buildable ArkTS project so that a requested behavior works end to end,...
This study explores an alternative condition-free analysis for the clustering quality of DCSC from a pure spectral view, without any random graph models, and proposes ASCENT (Adaptive Spectral Clustering with Node-wise correcTion), a simple yet effective extension of DCSC.
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