2 papers indexed here
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.
This paper shows that learned search can support arbitrary K with the preprocessing cost of a single top-1 model, and reduces total serving and preprocessing computation by up to 28%.
SMetric addresses session-centric scheduling with differential scheduling based on two indicators derived from the request itself, the session turn and the local KV\$ hit: it schedules first-turn requests for load balance, and sticks follow-ups to the instance with the highest local hit for high KV\$ reuse.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
