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Liang Pang

12 papers hereh-index 11479 citations19 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author12

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.IR11
  • cs.CL1
same name
  • Liang Pang — 55 papers, h 16
  • Liang Pang — 29 papers, h 20
  • Liang Pang — 7 papers, h 2
  • Liang Pang — 4 papers, h 3
  • Liang Pang — 3 papers, h 5
  • Liang Pang — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedBias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era

124 citations · 165 across the 12 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.IR2025★ 3 cited

NExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search

Sunhao Dai, Wenjie Wang, Liang Pang +4

Generative AI search is reshaping information retrieval by offering end-to-end answers to complex queries, reducing users' reliance on manually browsing and summarizing multiple we…

cs.IR2025

Understanding Accuracy-Fairness Trade-offs in Re-ranking through Elasticity in Economics

Chen Xu, Jujia Zhao, Wenjie Wang +4

Fairness is an increasingly important factor in re-ranking tasks. Prior work has identified a trade-off between ranking accuracy and item fairness. However, the underlying mechanis…

cs.CL2025

Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents

Haoyu Wang, Sunhao Dai, Haiyuan Zhao +6

Previous studies have found that PLM-based retrieval models exhibit a preference for LLM-generated content, assigning higher relevance scores to these documents even when their sem…

cs.IR2025

Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation

Chen Xu, Yuxin Li, Wenjie Wang +3

Group max-min fairness (MMF) is commonly used in fairness-aware recommender systems (RS) as an optimization objective, as it aims to protect marginalized item groups and ensures a…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.