Evidence map›Paper›PMID 40822049›Full record

ArticleProceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data2024

SEFD: Semantic-Enhanced Framework for Detecting LLM-Generated Text.

Weiqing He, Bojian Hou, Tianqi Shang, Davoud Ataee Tarzanagh, Qi Long, Li Shen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Weiqing HeSchool of Art and Science, University of Pennsylvania, Philadelphia, USA.
Bojian HouDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA.
Tianqi ShangDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Philadelphia, USA.
Davoud Ataee TarzanaghDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA.
Qi LongDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA.
Li ShenDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA.

Funding

Technology Identification and Training CoreP30AG073105 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DEMIRIS, GEORGE, KARLAWISH, JASON H · 2021 to 2025
$21.2M
NIA NIH HHS P30 AG073105
6 · The paper itself

Abstract

The widespread adoption of large language models (LLMs) has created an urgent need for robust tools to detect LLM-generated text, especially in light of

Indexed as

Information RetrievalLLM-Generated Text DetectionLLMsParaphrasingSemantic Analysis

Identifiers

PMID40822049
PMCPMC12352509

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.