Verified claim · AI-ML · 82% confidence
XLNet introduced in paper: XLNet: Generalized Autoregressive Pretraining for Language Understanding (Yang et al., 2019).
Last verified 2026-06-19 · Methodology veritas-v0.1 · d8983079997f21c6
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Structured fields
- Subject
- XLNet
- Predicate
introduced_in_paper- Object
- XLNet: Generalized Autoregressive Pretraining for Language Understanding (Yang et al., 2019)
- Confidence
- 82%
- Tags
- xlnet · generalized-autoregressive-pretraining · permutation-language-modeling · bidirectional-context · nlp · pretraining · 2019
Sources (2)
[1] preprint · arXiv (Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le) · 2019-06-19
XLNet: Generalized Autoregressive Pretraining for Language Understanding“In light of these pros and cons, we propose XLNet, a generalized autoregressive pretraining method that (1) enables learning bidirectional contexts by maximizing the expected likelihood over all permutations of the factorization order and (2) overcomes the limitations of BERT thanks to its autoregressive formulation.”
[2] docs · Hugging Face
XLNet: Generalized Autoregressive Pretraining for Language Understanding (Hugging Face Papers)Hugging Face is rated by SourceScore — see its reliability →
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XLNet introduced in paper: XLNet: Generalized Autoregressive Pretraining for Language Understanding (Yang et al., 2019). — SourceScore Claim d8983079997f21c6 (verified 2026-06-19). https://sourcescore.org/api/v1/claims/d8983079997f21c6.jsonEmbed this claim
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Yes — SourceScore verified this claim with 82% confidence as of 2026-06-19. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
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Evidence comes from 2 primary sources: arXiv (Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le), Hugging Face. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/d8983079997f21c6.json includes an HMAC-SHA256 signature for audit verification.
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// "XLNet introduced in paper: XLNet: Generalized Autoregressive Pretraining for Language Understanding (Yang et al., 2019)."Python
import httpx
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# "XLNet introduced in paper: XLNet: Generalized Autoregressive Pretraining for Language Understanding (Yang et al., 2019)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_xlnet_fact() -> dict:
"""Fetch the verified SourceScore claim for XLNet."""
r = httpx.get("https://sourcescore.org/api/v1/claims/d8983079997f21c6.json")
return r.json()