Author

Ziru Xu

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Jul 2026

Strategy-Aware Parameter-Efficient Adaptation for LLM-based Auto-Bidding

SAGE introduces a parameter-efficient multi-modal alignment framework for constrained auto-bidding with Large Language Models, demonstrating that SAGE consistently achieves superior performance while tuning less than 10% of the trainable parameters required by full fine-tuning.

Songyue Cai, Lian-Yu Wang, Shane Gu et al. · arXiv.org · 1 citation

Preprint Aug 2026

TransRetrieval: Scaling Up Transformer-Based Retrieval for Industrial Recommendation

TransRetrieval is presented, a Transformer-based retrieval framework that scales with both computational budget and cross-domain data and introduces weighted average aggregation, which restores the homogeneous-token assumption Transformers rely on, and target token compression that cuts per-candidate FLOPs while preserving cross-attention expressiveness.

Zhi-Fei Zheng, Yunfei Liu, Bin Liu et al. · 0 citations