Papers › Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation

Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation

15 Jun 2022arXiv:2206.07551archive 2025-07-28

JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon

Open-Set Domain Adaptation (OSDA) assumes that a target domain contains unknown classes, which are not discovered in a source domain. Existing domain adversarial learning methods are not suitable for OSDA because distribution matching with unknown classes leads to negative transfer. Previous OSDA methods have focused on matching the source and the target distribution by only utilizing known classes. However, this known-only matching may fail to learn the target-unknown feature space. Therefore, we propose Unknown-Aware Domain Adversarial Learning (UADAL), which aligns the source and the target-known distribution while simultaneously segregating the target-unknown distribution in the feature alignment procedure. We provide theoretical analyses on the optimized state of the proposed unknown-aware feature alignment, so we can guarantee both alignment and segregation theoretically. Empirically, we evaluate UADAL on the benchmark datasets, which shows that UADAL outperforms other methods with better feature alignments by reporting state-of-the-art performances.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2206.07551")

Code

Syntology Ran 19 of 23 code samples harvested from 4 repositories linked to this paper; 4 have no recorded run. Of those that ran: 7 ran · honoured contract; 1 ran · fixture could not drive it; 11 ran with no contract checked.

By repository: official repository: 11 samples from 1 repository, 10 ran; found in paper text by Syntology: 12 samples from 3 repositories, 9 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

joonho-jang/uadal officialmentioned in paperpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

23 samples harvested; 19 ran; 7 honoured the contract we drafted; 4 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

7ran · honoured contract
1ran · fixture could not drive it
11ran
4unverified

Licence: 11 of the 23 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from 4 repositories linked to this paper, official or community; each sample names its own and says which. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

BetaMixture1D joonho-jang/uadal/models/model_UADAL.py official repository ran no licence file found · pointer only · 5aa20ef89805f477 · report
ConstantScheduler joonho-jang/uadal/models/model_UADAL.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · f546f92da1455b06 · report
CosineScheduler joonho-jang/uadal/models/model_UADAL.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · 5347cf29668d0b0f · report
CrossEntropyLoss joonho-jang/uadal/models/model_UADAL.py official repository ran · fixture could not drive it fingerprinted no licence file found · pointer only · f608fa2fceb2a50c · report
HLoss joonho-jang/uadal/models/model_UADAL.py official repository ran fingerprinted no licence file found · pointer only · 46364372b95e3e54 · report
OptimWithSheduler joonho-jang/uadal/models/model_UADAL.py official repository ran no licence file found · pointer only · 48528d3e09cee383 · report
StepScheduler joonho-jang/uadal/models/model_UADAL.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · 36077ab7be923757 · report
fit_beta_weighted joonho-jang/uadal/models/model_UADAL.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · d8d7e01f0393c492 · report
inverseDecayScheduler joonho-jang/uadal/models/model_UADAL.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · 74e6be8aa01706d3 · report
weighted_mean joonho-jang/uadal/models/model_UADAL.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · 3e2e36c1b10b8499 · report
UADAL joonho-jang/uadal/models/model_UADAL.py official repository unverified no licence file found · pointer only · dea6c8d67cc0ca9f · report
AdversarialNetwork thuml/Separate_to_Adapt/networks.py found in paper text by Syntology ran · metamorphic tier: deterministic MIT (permissive) · f73e366b978d0a46 · report
EdgeUpdateNetwork BUserName/PGL/models/graphbase.py found in paper text by Syntology ran MIT (permissive) · 1be3f94367e35c2f · report
GradientReverseModule thuml/Separate_to_Adapt/networks.py found in paper text by Syntology ran · metamorphic tier: deterministic fingerprinted MIT (permissive) · 291a55b84ab7b46d · report
GraphNetwork BUserName/PGL/models/graphbase.py found in paper text by Syntology ran MIT (permissive) · 469e273dd44fecc7 · report
LargeAdversarialNetwork thuml/Separate_to_Adapt/networks.py found in paper text by Syntology ran · metamorphic tier: deterministic MIT (permissive) · 2a8f44b421d66127 · report
NodeUpdateNetwork BUserName/PGL/models/graphbase.py found in paper text by Syntology ran MIT (permissive) · 802b81f6275e505c · report
easy_dic Solacex/Domain-Consensus-Clustering/init_config.py found in paper text by Syntology ran MIT (permissive) · adc5e415cd269dea · report
to_cuda Solacex/Domain-Consensus-Clustering/utils/cdd.py found in paper text by Syntology ran · honoured contract fingerprinted MIT (permissive) · 00780a5caa71ae85 · report
type_align Solacex/Domain-Consensus-Clustering/init_config.py found in paper text by Syntology ran fingerprinted MIT (permissive) · 3ecaaabd66c84b40 · report
ExpWeight Solacex/Domain-Consensus-Clustering/trainer/dcc1_trainer.py found in paper text by Syntology unverified MIT (permissive) · 490b9538e2271517 · report
GradientReverseLayer thuml/Separate_to_Adapt/networks.py found in paper text by Syntology unverified MIT (permissive) · 00171f464fa4f231 · report
show_config Solacex/Domain-Consensus-Clustering/init_config.py found in paper text by Syntology unverified MIT (permissive) · 9fedc0c25832aa9b · report

Tasks

Domain Adaptation

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections