Chenlu Ding

2 accepted papers

2026

Delayed Feedback Modeling with Influence Functions

Chenlu Ding, Jiancan Wu, Yancheng Yuan, Cunchun Li, Xiang Wang, Dingxian Wang +2

AAAI 2026technical

In online advertising under the cost-per-conversion (CPA) model, accurate conversion rate (CVR) prediction is crucial. A major challenge is delayed feedback, where conversions may occur long after user interactions, leading to incomplete recent data and biased model training. Existing solutions part

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2025

Unified Parameter-Efficient Unlearning for LLMs

Chenlu Ding, Jiancan Wu, Yancheng Yuan, Jinda Lu, Kai Zhang, Alex Su +2

ICLR 2025poster

The advent of Large Language Models (LLMs) has revolutionized natural language processing, enabling advanced understanding and reasoning capabilities across a variety of tasks. Fine-tuning these models for specific domains, particularly through Parameter-Efficient Fine-Tuning (PEFT) strategies like…

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