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Zhen Qin

22 papers hereh-index 181.5k citations36 works total

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

author position
  • first author3
  • middle author19

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • cs.IR19
  • cs.CL2
  • cs.LG1
same name
  • Zhen Qin — 28 papers, h 12
  • Zhen Qin — 25 papers, h 15
  • Zhen Qin — 13 papers, h 40
  • Zhen Qin — 13 papers, h 4
  • Zhen Qin — 13 papers, h 7
  • Zhen Qin — 10 papers, h 4

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
20202026
most citedNon-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction

24 citations · 99 across the 22 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CL2024

Integrating Planning into Single-Turn Long-Form Text Generation

Yi Liang, You Wu, Honglei Zhuang +8

Generating high-quality, in-depth textual documents, such as academic papers, news articles, Wikipedia entries, and books, remains a significant challenge for Large Language Models…

cs.CL2024★ 3 cited

Inference Scaling for Long-Context Retrieval Augmented Generation

Zhenrui Yue, Honglei Zhuang, Aijun Bai +7

The scaling of inference computation has unlocked the potential of long-context large language models (LLMs) across diverse settings. For knowledge-intensive tasks, the increased c…

cs.IR2024★ 3 cited

Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I

Harrie Oosterhuis, Rolf Jagerman, Zhen Qin +2

The traditional evaluation of information retrieval (IR) systems is generally very costly as it requires manual relevance annotation from human experts. Recent advancements in gene…

cs.IR2024

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing

Le Yan, Zhen Qin, Honglei Zhuang +4

The powerful generative abilities of large language models (LLMs) show potential in generating relevance labels for search applications. Previous work has found that directly askin…

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