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Qingfu Zhu

4 papers here

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.CL3
  • cs.LG1
ORCID 0000-0003-3395-222X
same name
  • Qingfu Zhu — 11 papers
  • Qingfu Zhu — 3 papers
  • Qingfu Zhu — 2 papers
  • Qingfu Zhu — 1 paper, h 10
  • Qingfu Zhu — 1 paper
  • Qingfu Zhu — 1 paper

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
20162025
most citedA Static and Dynamic Attention Framework for Multi Turn Dialogue Generation

15 citations · 30 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2025★ 6 cited

Advancing Tool-Augmented Large Language Models via Meta-Verification and Reflection Learning

Zhiyuan Ma, Jiayu Liu, Xianzhen Luo +3

Empowering large language models (LLMs) with effective tool utilization capabilities is crucial for enabling AI agents to solve complex problems. However, current models face two m…

cs.LG2025

Think Before You Accept: Semantic Reflective Verification for Faster Speculative Decoding

Yixuan Wang, Yijun Liu, Shiyu ji +4

Large language models (LLMs) suffer from high inference latency due to the auto-regressive decoding process. Speculative decoding accelerates inference by generating multiple draft…

cs.CL2024★ 15 cited

A Static and Dynamic Attention Framework for Multi Turn Dialogue Generation

Wei-Nan Zhang, Yiming Cui, Kaiyan Zhang +4

Recently, research on open domain dialogue systems have attracted extensive interests of academic and industrial researchers. The goal of an open domain dialogue system is to imita…

cs.CL2016★ 9 cited

Learning to Start for Sequence to Sequence Architecture

Qingfu Zhu, Weinan Zhang, Lianqiang Zhou +1

The sequence to sequence architecture is widely used in the response generation and neural machine translation to model the potential relationship between two sentences. It typical…

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