Papers by Yiting Shen

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Challenge:	Existing benchmarks focus on direct queries for a factual answer, but fail to evaluate the more crucial capability of actively applying memory to execute tasks.
Approach:	They propose a benchmark to evaluate whether agents can proactively leverage long-term memory to execute tool-based actions by selecting appropriate tools and grounding their parameters.
Outcome:	The proposed benchmarks show that 91.3% of tasks are memory-dependent . the benchmarks simulate persistent assistant usage, where users mention the same topic across long, interrupted interactions and expect previously established preferences and task states to be implicitly applied.