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researcher

Yushan Pan

4 papers hereh-index 352 citations11 works total

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1
  • cs.IR1
same name
  • Yushan Pan — 3 papers, h 7
  • Yushan Pan — 2 papers, h 2
  • Yushan Pan — 2 papers, h 1
  • Yushan Pan — 1 paper, h 1
  • Yushan Pan — 1 paper, h 2
  • Yushan Pan — 1 paper, h 7

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

most citedRDSA: A Robust Deep Graph Clustering Framework via Dual Soft Assignment

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2025

FinDebate: Multi-Agent Collaborative Intelligence for Financial Analysis

Tianshi Cai, Guanxu Li, Nijia Han +10

We introduce FinDebate, a multi-agent framework for financial analysis, integrating collaborative debate with domain-specific Retrieval-Augmented Generation (RAG). Five specialized…

cs.LG2024★ 2 cited

RDSA: A Robust Deep Graph Clustering Framework via Dual Soft Assignment

Yang Xiang, Li Fan, Tulika Saha +4

Graph clustering is an essential aspect of network analysis that involves grouping nodes into separate clusters. Recent developments in deep learning have resulted in graph cluster…

cs.IR2024

Document Set Expansion with Positive-Unlabelled Learning Using Intractable Density Estimation

Haiyang Zhang, Qiuyi Chen, Yuanjie Zou +3

The Document Set Expansion (DSE) task involves identifying relevant documents from large collections based on a limited set of example documents. Previous research has highlighted…

cs.LG2024

Document Set Expansion with Positive-Unlabeled Learning: A Density Estimation-based Approach

Haiyang Zhang, Qiuyi Chen, Yuanjie Zou +3

Document set expansion aims to identify relevant documents from a large collection based on a small set of documents that are on a fine-grained topic. Previous work shows that PU l…

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