We have 3 of 7 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
NLPG is proposed, an external policy-memory method for improving a fixed agent without changing its model parameters or program structure that outperforms the strongest listed baseline for each benchmark by 8.71 percentage points on average.
TRACER is proposed, which formulates compression as a sequential per-tool decision problem, and demonstrates the value of consequence-aware, per-tool context retention for improving the efficiency of long-horizon language agents.
This work presents DREAM (Developing Recommender Engine with Agentic Methods), an autonomous optimization control architecture that adds a perception-aware, orchestrable, and auditable policy layer atop existing pipelines without replacing them, supporting agentic meta-control as a viable paradigm for industrial recomm...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
