◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Meng Cao

14 papers here

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

author position
  • first author6
  • middle author8

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV5
  • cs.CL4
  • cs.LG2
  • cs.CY1
  • cs.IR1
  • math.DS1
ORCID 0000-0002-1008-5509
same name
  • Meng Cao — 7 papers, h 14
  • Meng Cao — 2 papers
  • Meng Cao — 2 papers
  • Meng Cao — 1 paper
  • Meng Cao — 1 paper
  • Meng Cao — 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
20142024
most citedLatent Heterogeneous Graph Network for Incomplete Multi-View Learning

71 citations · 91 across the 14 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2023★ 1 cited

Responsible AI Considerations in Text Summarization Research: A Review of Current Practices

Yu Lu Liu, Meng Cao, Su Lin Blodgett +3

AI and NLP publication venues have increasingly encouraged researchers to reflect on possible ethical considerations, adverse impacts, and other responsible AI issues their work mi…

cs.CL2023

Successor Features for Efficient Multisubject Controlled Text Generation

Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung +1

While large language models (LLMs) have achieved impressive performance in generating fluent and realistic text, controlling the generated text so that it exhibits properties such…

cs.CL2023★ 2 cited

Systematic Rectification of Language Models via Dead-end Analysis

Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung +1

With adversarial or otherwise normal prompts, existing large language models (LLM) can be pushed to generate toxic discourses. One way to reduce the risk of LLMs generating undesir…

cs.CL2023★ 1 cited

Learning with Rejection for Abstractive Text Summarization

Meng Cao, Yue Dong, Jingyi He +1

State-of-the-art abstractive summarization systems frequently hallucinate content that is not supported by the source document, mainly due to noise in the training dataset. Existin…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.