Papers by Zhanshuo Cao
Length-Induced Embedding Collapse in PLM-based Models (2025.acl-long)
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| Challenge: | In text embeddings from PLMs are essential for many NLP applications, but performance degrades on longer texts. |
| Approach: | They propose a method which mitigates the phenomenon of Length Collapse . they propose TempScale to ensure more consistent embeddings across different text lengths . |
| Outcome: | The proposed method improves performance on MTEB and LongEmbed by 0.94% on short and 1.10% on long texts. |
Media Source Matters More Than Content: Unveiling Political Bias in LLM-Generated Citations (2025.emnlp-main)
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| Challenge: | generative search engines rely on in-line citations as the key gateway to original webpages . a recent study shows that LLMs tend to cite left-leaning sources at higher rates compared to traditional retrieval systems . |
| Approach: | They construct a dataset of news articles labeled with left- or right-leaning stances . they find that LLMs tend to cite left-leansing sources at higher rates than traditional retrieval systems . |
| Outcome: | The proposed dataset shows that LLMs tend to cite left-leaning sources at higher rates than traditional retrieval systems. |