4 papers · 1 filter
Every Cache Entry Earns Its Place: Global Allocation of Resolution and Coverage for KV Cache Compression
Haolin Tian, Yuzhe Liu, Tonghan Wang
As large language models (LLMs) process increasingly long contexts, KV cache storage and repeated access have become a major bottleneck. Existing KV cache compression methods rely…
NaiAD: Initiate Data-Driven Research for LLM Advertising
Yihang Zhang, Zimeng Huang, Ren Zhai +2
Reconciling platform revenue with user experience in LLM advertising motivates a data-centric foundation. We introduce NaiAD, the first comprehensive dataset for LLM-native adverti…
LLM Advertisement based on Neuron Auctions
Peiran Yun, Wenxin Xu, Jiayuan Liu +4
As Large Language Models (LLMs) transition into conversational agents, generative advertising emerges as a crucial monetization strategy. However, embedding advertisements within u…
Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
Lingkai Kong, Haichuan Wang, Tonghan Wang +2
Incorporating pre-collected offline data can substantially improve the sample efficiency of reinforcement learning (RL), but its benefits can break down when the transition dynamic…