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Haoyu Wang

4 papers hereh-index 341 citations10 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
same name
  • Haoyu Wang — 35 papers, h 13
  • Haoyu Wang — 15 papers, h 7
  • Haoyu Wang — 11 papers, h 2
  • Haoyu Wang — 11 papers, h 4
  • Haoyu Wang — 10 papers, h 5
  • Haoyu Wang — 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
20242026
collaborators

4 papers

cs.CL2026

OMGEval: An Open Multilingual Generative Evaluation Benchmark for Large Language Models

Yang Liu, Meng Xu, Shuo Wang +7

Modern large language models (LLMs) should generally benefit individuals from various cultural backgrounds around the world. However, most recent advanced generative evaluation ben…

cs.CL2026

LLM×MapReduce-V3: Enabling Interactive In-Depth Survey Generation through a MCP-Driven Hierarchically Modular Agent System

Yu Chao, Siyu Lin, xiaorong wang +7

We introduce LLM x MapReduce-V3, a hierarchically modular agent system designed for long-form survey generation. Building on the prior work, LLM x MapReduce-V2, this version incorp…

cs.CL2025

LLM×MapReduce-V2: Entropy-Driven Convolutional Test-Time Scaling for Generating Long-Form Articles from Extremely Long Resources

Haoyu Wang, Yujia Fu, Zhu Zhang +8

Long-form generation is crucial for a wide range of practical applications, typically categorized into short-to-long and long-to-long generation. While short-to-long generations ha…

cs.CL2024

LLM×MapReduce: Simplified Long-Sequence Processing using Large Language Models

Zihan Zhou, Chong Li, Xinyi Chen +11

Enlarging the context window of large language models (LLMs) has become a crucial research area, particularly for applications involving extremely long texts. In this work, we prop…

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