揭秘查询时序让大模型与人类产生相反位置偏好的新发现，获奖论文值得一读。
arXiv:2608.12387v1 Announce Type: cross Abstract: Positional biases such as recency and primacy effects have been documented in large language models …
揭秘LLM作为评判者时的位置偏差，点式与对式评估究竟何者更准确？
arXiv:2602.02219v2 Announce Type: replace Abstract: Large language models are widely employed as evaluators, a paradigm commonly referred to as LLM-as…
揭秘扩散LLM中查询位置导致的关键偏见，并提出基于解码动态的消除方法。
arXiv:2606.19349v1 Announce Type: cross Abstract: While In-Context Learning (ICL) is extensively studied in Autoregressive (AR) LLMs, its mechanism wi…
系统性评估多模态大模型在多视频摘要中的位置偏差，揭示排序影响生成质量的规律。
arXiv:2606.04596v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used for video understanding, yet their reli…
揭示长上下文LLM因位置偏差导致推理失败的盲点，挑战现有基准评估体系。
arXiv:2605.23170v1 Announce Type: cross Abstract: Position-controlled evaluation is standard for retrieval tasks such as Needle-in-a-Haystack and RULE…