This work proposes a Causal auto-Bidding method based on a Diffusion completer-aligner framework, termed CBD, which achieves superior performance on large-scale auto-bidding benchmarks, but also delivers significant improvements on an online advertising platform, including a 2.0% increase in target cost.
Ye-Wen Li, Jingtong Gao, Peng Jiang et al.· Proceedings of the 32nd ACM...· 0 citations
AgentX-Model, the next generation of AgentX's model research framework, is presented, which connects proposal development and model experimentation within sandboxes defined by business inputs and prediction tasks within sandboxes defined by business inputs and prediction tasks.
Shuang Yang, Zi-Jie Zhuang, Chang-Xin Lao et al.· 0 citations
A feedback-driven agent framework is proposed that first induces task-oriented intent and then discovers recommendation policies according to their incremental utility over an intent-only baseline, enabling LLM-free online inference.
Zhi Chen, Minmao Wang, Xing-Chen Liu et al.· arXiv.org· 0 citations
WhisperRec compresses teacher-generated CoT into learnable latent reasoning tokens, enabling a Latent-Reason-then-Answer paradigm that performs reasoning in latent space without producing verbose rationales, and achieves over 10x higher online inference throughput.
Hao Jiang, Pei Du, Pengfei Yao et al.· arXiv.org· 0 citations
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