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Junbang Huo

4 papers hereh-index 19 citations5 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.IR3
  • q-fin.PR1

identity via Semantic Scholar / OpenAlex

most citedStock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory

7 citations · 7 across the 4 of their papers we have counts for

collaborators

4 papers

cs.IR2026

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent

Xinxun Zhang, Yuling Xiong, Yangru Huang +14

Generative Recommendation (GR) reformulates recommendation as next-token generation over item Semantic IDs (SIDs) and has shown promise in industrial applications. However, extendi…

cs.IR2026

Tencent Advertising Algorithm Challenge 2025: All-Modality Generative Recommendation

Junwei Pan, Wei Xue, Chao Zhou +20

Generative recommender systems are rapidly emerging as a new paradigm for recommendation, where collaborative identifiers and/or multi-modal content are mapped into discrete token…

cs.IR2026

DiffuReason: Bridging Latent Reasoning and Generative Refinement for Sequential Recommendation

Jie Jiang, Yang Wu, Qian Li +6

Latent reasoning has emerged as a promising paradigm for sequential recommendation, enabling models to capture complex user intent through multi-step deliberation. Yet existing app…

q-fin.PR2021★ 7 cited

Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory

Mingwen Liu, Junbang Huo, Yulin Wu +1

This paper intends to apply the Hidden Markov Model into stock market and and make predictions. Moreover, four different methods of improvement, which are GMM-HMM, XGB-HMM, GMM-HMM…

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