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Author

Hongyuan Zhan

3 papers indexed here

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Many-Tier Instruction Hierarchy in LLM Agents

This work proposes Many-Tier Instruction Hierarchy (ManyIH), a paradigm for resolving instruction conflicts among instructions with arbitrarily many privilege levels, and introduces ManyIH-Bench, the first benchmark for ManyIH.

Jing-Yu Zhang, Tian-Jian Li, William Jurayj et al. · 9 citations

Positional Encoding via Token-Aware Phase Attention

Token-Aware Phase Attention (TAPA) is introduced, a new positional encoding method that incorporates a learnable phase function into the attention mechanism and attains substantially lower perplexity and stronger retrieval performance in the long-context regime than RoPE-style baselines.

Yu Wang, Sheng Shen, Rémi Munos et al. · 2 citations

Large Reasoning Models Learn Better Alignment from Flawed Thinking

RECAP (Robust Safety Alignment via Counter-Aligned Prefilling), a principled reinforcement learning (RL) method for post-training that explicitly teaches models to override flawed reasoning trajectories and reroute to safe and helpful responses, substantially improves safety and jailbreak robustness, reduces overrefusa...

Sheng-Hsuan Peng, E. Smith, Ivan Evtimov et al. · 10 citations · ⚡2

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