Papers by Yuying Chen

3 papers
HierDiffuse: Progressive Diffusion for Robust Interest Fusion in CTR Prediction (2025.emnlp-industry)

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Challenge: Existing approaches fuse long-term behavioral profiles and short-term interactions, suffering from representational misalignment and noise in transient signals.
Approach: They propose a framework that redefines interest fusion as a hierarchical denoising process through diffusion models.
Outcome: The proposed framework redefines interest fusion as a hierarchical denoising process through diffusion models.
GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal Reasoning (2026.findings-acl)

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Challenge: Recent reinforcement learning approaches have advanced reasoning in Large Language Models (LLMs), yet their adaptation to multimodal LLMs remains underexplored.
Approach: They propose a reinforcement learning framework that eliminates KL penalties and rewards consistency . they propose GRPO-CARE, which outperforms standard GR PO, with a base reward for accuracy and an adaptive bonus for consistency.
Outcome: The proposed framework outperforms standard GRPO on the most difficult evaluation level and reasoning consistency test benchmarks.
Root Defense Strategies: Ensuring Safety of LLM at the Decoding Level (2025.acl-long)

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Challenge: Existing methods to detect harmful outputs from prefill-level lacks utilization of the model’s decoding outputs, leading to relatively lower effectiveness and robustness.
Approach: They propose a robust decoding mechanism that corrects harmful queries directly rather than rejecting them outright.
Outcome: The proposed model improves model security without compromising reasoning speed.

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