Pith. sign in

Paper Citation Record · LEDGER

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning

As of 9 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2508.21816.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.21816 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:00:29.035049Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

  • verified exact4
  • verified fuzzy32
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b3bc631b-bfac-45f9-928e-1c8743aca8ba · outbound

This paper cites Multi-Label Learning from Single Positive Labels.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Multi-Label Learning from Single Positive Labels

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:00:29.689840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.168343Z digest=sha256:3cfabfac1e79f54d3a1ce07263ca16de0cf1551d0039167fef061ce0a9c2c0a2

Observation 3cca6bd9-4766-4c90-82ab-90e13d18b081 · outbound

This paper cites A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:36.724724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.252620Z digest=sha256:10dc6d046f48faf44ac697e314cfc20b35a40e0b3a40048cb6e71b7d1830eebd

Observation 1e7067e1-111b-4857-adcd-dd1023e3ed34 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Explaining and Harnessing Adversarial Examples

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:25.349258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:25.349258Z digest=sha256:285469d5524179b34e29b25d94988f9b07ac6194c37026fb3ca42301cfcf0d55

Observation 4427c675-c45a-4919-82ac-c95f8fbc5bf1 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:25.453646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:25.453646Z digest=sha256:136cbd753477d25a5b20e62d720a35f874432b23d6f356740bd504f4ed2bf1c3

Observation eceff757-f62b-4ecd-8788-c9d6194d92b2 · outbound

This paper cites Generative adversarial nets,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Generative adversarial nets,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:25.548507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:25.548507Z digest=sha256:ebb285d54e63e384c7d9e8350c52589528a266519dbc30c1abb9f703a9f39296

Observation 4b95fbdc-1f24-426d-9f2f-0e744768a82c · outbound

This paper cites Gandef: A gan based adversarial training defense for neural network classifier,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Gandef: A gan based adversarial training defense for neural network classifier,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:36.569249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.614562Z digest=sha256:6394af59abd20e610f8ef0376aeb1dc7bc7ac98ae60c8fda16a31e4f44c5b663

Observation f069217e-f805-45ad-b137-0e4c26e8de16 · outbound

This paper cites Denoising diffusion probabilistic models,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Denoising diffusion probabilistic models,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:25.677460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:25.677460Z digest=sha256:37cb3da997187b0ae35a36c13d50793e83a8a79e29977208ad6dd32a12e41dca

Observation 787ff73c-67c5-4585-b640-1255710d37b0 · outbound

This paper cites Weakly supervised multi-label learning via label enhancement.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Weakly supervised multi-label learning via label enhancement

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:36.437199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.744961Z digest=sha256:6f6a8c1076b7532e65553cae211bc276356998e21f9459dfa93a504fd2938b27

Observation eb0fced3-2392-449b-854f-e64658ab683e · outbound

This paper cites Multi-label learning from single positive labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Multi-label learning from single positive labels,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:36.287745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.840766Z digest=sha256:2ae6ba6a9b4917a82bb3e612fe69c5df8d7726efacf39d92e915afbd3fcf419e

Observation 560d2b12-f7ab-452a-bff7-36e0cbd44d77 · outbound

This paper cites When does label smoothing help?.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning When does label smoothing help?

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:36.106608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.918210Z digest=sha256:8cb8b3a765740ec8c2a6caf885671c9714c253184f970766d83337932e60379a

Observation 4788ac9a-b604-41e0-8ec3-12a9d68e1207 · outbound

This paper cites Simple and Robust Loss Design for Multi-Label Learning with Missing Labels.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Simple and Robust Loss Design for Multi-Label Learning with Missing Labels

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:00:29.553750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:25.992001Z digest=sha256:5ff3b8868f07d7a2fef3d0e1e74f05cb872c8abe6687b62f5017b5a094b6a61e

Observation 7be568f5-1131-445f-b2e2-a772b7dd87f2 · outbound

This paper cites Large loss matters in weakly supervised multi-label classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Large loss matters in weakly supervised multi-label classification,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:35.951828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.063810Z digest=sha256:4bc3e5e0e49d6377c541f8424558fc5bd61f837869471e18c27c5bcf0b83ad16

Observation 1fe40f3a-4984-4539-b72f-534890a31d2d · outbound

This paper cites Bridging the gap between model explanations in partially annotated multi-label classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Bridging the gap between model explanations in partially annotated multi-label classification,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:35.781148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.148597Z digest=sha256:3975bea03d165d27d238a43d2073b6beed2147f529b40a5a2e84a295b3561835

Observation fe4af609-53e3-4c13-8ebf-81d4d64da884 · outbound

This paper cites Exploring structured semantic prior for multi label recognition with incomplete labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Exploring structured semantic prior for multi label recognition with incomplete labels,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:35.586223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.217749Z digest=sha256:117a9ee012b6a71d2c815aabb8ba12a950bc28be4494fefd26dd772de9989393

Observation bc63184c-0758-42e4-be65-94e086a67600 · outbound

This paper cites Revisiting pseudo-label for single- positive multi-label learning,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Revisiting pseudo-label for single- positive multi-label learning,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:35.462034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.290459Z digest=sha256:24c8bd1c090abbdd32f54d1d8492fa20fe4c78f075f8af61fabc5a34ccfcc8ea

Observation 61c5cadc-f7f1-4657-ab97-e7a85dcfee40 · outbound

This paper cites Hierarchical prompt learning using clip for multi-label classification with single positive labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Hierarchical prompt learning using clip for multi-label classification with single positive labels,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:35.316036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.396125Z digest=sha256:6c8f92d9c736b124d6f9f00d4a34aea6d812d7e51c8c45ac4ea621fbfbe9b7ca

Observation c979f590-c09e-4d8e-bc65-4b3b14f12be7 · outbound

This paper cites Clipsitu: Effectively leveraging clip for conditional predictions in situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Clipsitu: Effectively leveraging clip for conditional predictions in situation recognition,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:35.137717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.482323Z digest=sha256:5cfe1431ccc86de7acc40548a7b594bad68c646f99c23955faa33ca295f68add

Observation 88750a55-50d5-4d29-94a4-1b42dc6ff9a1 · outbound

This paper cites Clip-event: Connecting text and images with event structures,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Clip-event: Connecting text and images with event structures,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:34.936670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.574086Z digest=sha256:e0c99188950ca0e9c4080ee38a5da0d333bb0b5a1e063ef69914374e5504d20f

Observation a0af5346-40a3-41f0-bc98-dcecb3eba770 · outbound

This paper cites Recurrent models for situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Recurrent models for situation recognition,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:34.623100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.678132Z digest=sha256:8e66a99498d86b0ae73a3b91a9999794f7e1886f4bb58255b1ebe7ad925e4805

Observation 3e2aa608-4fff-43ff-87e5-ee4e251fc0fe · outbound

This paper cites Situation recognition with graph neural networks,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Situation recognition with graph neural networks,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:34.367688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.781700Z digest=sha256:7c33e155715e9e7b7270aee91dff908a9e398f51197bfba6a5e4ec91901bbea4

Observation 36e4a13c-f04a-4a60-8fac-3d1ccfae8ec3 · outbound

This paper cites Mixture-kernel graph attention network for situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Mixture-kernel graph attention network for situation recognition,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:34.166410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.869730Z digest=sha256:fade92086ac62e9ceb0702ef535faa12bfd7296835ecbbfbf88c721caca8caf4

Observation e3702411-b182-4f65-b5b0-b7be96bd8a4d · outbound

This paper cites Attention-based context aware reasoning for situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Attention-based context aware reasoning for situation recognition,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:33.936378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:26.960421Z digest=sha256:578339a174b84e3ea789a4dea622e45f2419198a19176c716396f75bdbbe682c

Observation 0aef7c4f-5b06-4df0-a4d0-c677e2d58d19 · outbound

This paper cites Collaborative transformers for grounded situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Collaborative transformers for grounded situation recognition,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:33.654292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.031267Z digest=sha256:77ccfca2d7c712cc19c6d6f2d08619214bd28da3a738a1493d376eaa08aa8dea

Observation 8d86edae-7b35-4958-af9c-f72d744dd95b · outbound

This paper cites Ambiguous images with human judgments for robust visual event classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Ambiguous images with human judgments for robust visual event classification,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:33.434991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.110005Z digest=sha256:62c97bb1096b4d1b71b8f70624e0783d1a4f7c37566e8edee2baa0c4295ce3ec

Observation f5562153-c366-4a73-b521-1f512cdb0f8c · outbound

This paper cites Situation recognition: Visual semantic role labeling for image understanding,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Situation recognition: Visual semantic role labeling for image understanding,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:33.232424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.195675Z digest=sha256:5ad6faf70d8d1c76b8d76ca531e9ed2a5991a829d556ef7adf857bbdd22248ca

Observation f51a0f79-625b-46e6-b489-b8f1558be31f · outbound

This paper cites Grounded situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Grounded situation recognition,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:33.035137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.265523Z digest=sha256:6406362dd4df2d62aadc49259dd349929601875ac318ade76662c096d0c8e0a5

Observation 4b7ee070-7bd5-4fb6-9f97-ddf5855b9466 · outbound

This paper cites an unresolved cited work.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-05T14:00:32.838176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.329280Z digest=sha256:fcd2db88cdc67daf749388b742460e337c8ba0ad8d3f6fb0c31d9520981972e0

Observation 7c5a591f-2667-4617-bec7-2ae008701445 · outbound

This paper cites Grounded Situation Recognition with Transformers.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Grounded Situation Recognition with Transformers

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:00:29.393255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.390648Z digest=sha256:7cfe4e8b0f897e7068e8319a767d946ea7acbc848daee53b9ba394748ff4ec54

Observation 96c1f74e-8c7a-49c8-a090-01f78aa292f5 · outbound

This paper cites Visualizing data using t-sne.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Visualizing data using t-sne

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:32.544582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.421574Z digest=sha256:7e40db07aabd83b6990570a5b21e926da8be541223849ecdd689e5a9b3690079

Observation 679c7ad0-de75-4677-8671-28342b7f5cf7 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:27.546533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:27.546533Z digest=sha256:f0ab79cca21aa0c1f1abdab1941b45a89dd3207825b9c8586ec6e635ddd996cb

Observation a131e26a-789f-4183-96b1-1e054a0ae782 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Learning transferable visual models from natural language supervision,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:27.642155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:27.642155Z digest=sha256:778db1808361a7c8306a56e83e854a1091e03b86afe5e7b09e193911fddcdc5a

Observation 19e1c319-a3a9-42c0-8624-3cbf1d86fcc3 · outbound

This paper cites The framenet database and software tools.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning The framenet database and software tools

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:32.252720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.715311Z digest=sha256:094edecb4e1b7cf04c8a272006f7b30feb3bfa128485d7372d3ec8b98d585307

Observation 194c5fab-0790-4fd9-aeda-4caf04c6fe8b · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:27.779710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:27.779710Z digest=sha256:56560bface31bdc63061f2341cfae60e9f2a8ac9c30a88b99f06cf8755e5f038

Observation 7c20bf85-8f9a-4254-bd8e-5338cf8a750f · outbound

This paper cites Focal loss for dense object detection,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Focal loss for dense object detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:32.111021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.846817Z digest=sha256:a644e3c3ac5f92977a0f963889d31b69d865fa8ac170007683682c8b1ceb72a6

Observation 4e69657e-6341-4838-8053-a4cfca86f47f · outbound

This paper cites Learning deep features for discriminative localization,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Learning deep features for discriminative localization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:31.901417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:27.938811Z digest=sha256:cdd706ec04fd4ce2e30b1c6522bd63462f96a03a2fcf5745a474376f9aecb62d

Observation acabd923-a3ed-412d-b848-3f91743aac51 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning The cityscapes dataset for semantic urban scene understanding,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:28.004562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:28.004562Z digest=sha256:f1e88bd5c42adcbf21cbb18212ab060245c6f3f6ed08fe0e80416395620fdc91

Observation a3ca3ef0-6ece-4057-92a1-cb25df5a9bba · outbound

This paper cites Activitynet: A large-scale video benchmark for human activity under- standing,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Activitynet: A large-scale video benchmark for human activity under- standing,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:31.673931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.095696Z digest=sha256:164088dba5c24cf9909e8f98a26f455cabc85517f00e69e647c5f475f4b4e3d2

Observation b1bcdeb3-f3da-47b1-ad7b-410428e175ad · outbound

This paper cites A survey on deep learning-driven remote sensing image scene understanding: Scene classification, scene retrieval and scene-guided object detection,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning A survey on deep learning-driven remote sensing image scene understanding: Scene classification, scene retrieval and scene-guided object detection,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:31.440025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.195915Z digest=sha256:a1a7c1e9987597234c77cf1c1d91eabdfa62b8a8092577bb9aed6ded5fed298d

Observation 197738d3-1dcb-42bb-9093-8a258da9175c · outbound

This paper cites Learning and understanding dynamic scene activity: a review,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Learning and understanding dynamic scene activity: a review,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:31.164875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.312423Z digest=sha256:a1e4e8f0c44c3e7c6ed927c28133bf0db39dd68382da97c0fd920a90a24446d0

Observation 0a1067c8-f87b-4e85-82ff-362b476daf96 · outbound

This paper cites Acknowledging the unknown for multi-label learning with single positive labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Acknowledging the unknown for multi-label learning with single positive labels,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:30.967763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.378086Z digest=sha256:002f238792befee5f0743917364572a9635c1738645b7c42d2744c5db499bff6

Observation 2c0c599e-4ce5-4bed-b20c-59c4a757aedd · outbound

This paper cites One positive label is sufficient: Single-positive multi-label learning with label enhance- ment,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning One positive label is sufficient: Single-positive multi-label learning with label enhance- ment,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:30.632068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.484918Z digest=sha256:915a8f9d803613dc5e3b57a725a37f8308b7af2a5d466a81b2cd1b8be0f68775

Observation 2d1e69e7-f160-4b9b-9069-a90672ca493c · outbound

This paper cites Qwen2.5-VL Technical Report.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Qwen2.5-VL Technical Report

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:28.597477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:28.597477Z digest=sha256:b172e9eb03b79cbbeeb16587b8194f4cdecb524b09fe744860cccb50237e5b37

Observation 1f514fc1-8a44-4978-b80d-506552c8548e · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:28.677090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:28.677090Z digest=sha256:3f8d5d09b973344a9c01e3abd29cfadce7bdd8ed22e2cc038c7cc856ecfd8b85

Observation 397bad29-138d-4473-9007-350d0f70e30f · outbound

This paper cites Deepseek-v3 technical report,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Deepseek-v3 technical report,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:30.323236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.726048Z digest=sha256:d9a1b23e05cf09499f9efdbbe001abe3c3e7d6a4e11ac24ed35bba07806ec4d5

Observation 564f2a3d-9ad8-4e96-948f-9efb1109c8aa · outbound

This paper cites Co-pseudo labeling and active selection for fundus single-positive multi-label learning,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Co-pseudo labeling and active selection for fundus single-positive multi-label learning,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:29.943608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.944626Z digest=sha256:3bdda3b2e7fbca14f2e15f5bf72f0b468a399b2d5418af18b029ad2fe446a183

Observation eaecc5f3-beec-4f6c-9783-53e8c9bd079b · outbound

This paper cites Semantic-guided Representation Learning for Multi-Label Recognition.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Semantic-guided Representation Learning for Multi-Label Recognition

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:00:29.188657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:28.855542Z digest=sha256:daa0655110d31a7b17c3a1d810f7623deccbbcba346038137ca59c254f09f5ce

Observation 48e8089d-8b49-4bff-a60d-ec15099a1401 · outbound

This paper cites Splicemix: A cross-scale and semantic blending augmentation strategy for multi-label image classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Splicemix: A cross-scale and semantic blending augmentation strategy for multi-label image classification,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:00:29.825348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:00:29.035049Z digest=sha256:536d268450a8f0259bbff3b023392752ff2dba6fb0b42b0aada8d619ccf047aa

Observation 5c5c8a58-0add-4302-af60-35d174c29280 · outbound

This paper cites DeepSeek-V3 Technical Report.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning DeepSeek-V3 Technical Report

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T14:00:28.796823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:00:28.796823Z digest=sha256:08a46c949af6ece3d61132c4ed618dfa98e1d29925f413869c170b5a318b29da

Pith citing papers

No inbound Pith citation observations are available.