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Zizhuo Fu

2 accepted papers

2026

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse

ICML 2026poster

Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several recent approaches aim to address this issue, including Sink Attention in GPT-OSS and Gated Attention in Qwen3-Next. However, a comprehensive analysis of the rela…

Cited by 0SourceScholar
2025

PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models

NeurIPS 2025poster

Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task oversimplification, data contamination, and flawed evaluation items. These deficiencies necessitate more rigorous assessment methods. To address these limitations, we intro…

Cited by 0SourceScholar