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Paper Citation Record · LEDGER

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

As of 20 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 3 inbound Pith citation observations for arXiv:2412.14097.

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

pith.paper-citation-record.v1
2412.14097 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:35:00.616605Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:17:03.837201Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:19:30.857615Z

Reference resolution

53 of 53 outbound references displayed

  • verified exact1
  • verified fuzzy31
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e00b22a-50e4-460a-b8cd-d446d7734907 · outbound

This paper cites write newline.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-11T12:35:00.472657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.472657Z digest=sha256:fd6d5ed6a099a04bd88b5f107ab72ad0624ba221b89b1fb3327458c4a6c892eb

Observation 79e0c6d1-5050-450f-85e6-c20d258daa41 · outbound

This paper cites Meaningfully debugging model mistakes using conceptual counterfactual explanations.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Meaningfully debugging model mistakes using conceptual counterfactual explanations

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.072722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.476679Z digest=sha256:2a39536796c46e89b5bc85946e5049a3f8553e2fd032b88b3468826defd1d0ed

Observation 4f15b561-1398-47d3-9846-4a447c220dd6 · outbound

This paper cites Debugging tests for model explanations.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Debugging tests for model explanations

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.064993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.479503Z digest=sha256:93fec5d19a616d83f7379ef711b7d4aceb2a3ddeedec42d83bd7e633c6f67052

Observation a64ef1a4-cde3-4330-b57e-201f9b165ca1 · outbound

This paper cites Zero-shot robustification of zero-shot models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Zero-shot robustification of zero-shot models

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.055991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.482626Z digest=sha256:f04ba3c667b3946bf248469e493bc95137d09a67ef7f33f9e4b55ffab3fc591e

Observation cdb6957b-b152-43c7-97af-06f5b79ab5cf · outbound

This paper cites Deep learning for segmentation of brain tumors: Impact of cross-institutional training and testing.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Deep learning for segmentation of brain tumors: Impact of cross-institutional training and testing

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.046492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.485644Z digest=sha256:c657829804790900471f00b7da0056ce26408bed2f0e30aaf92df82b3d1d6229

Observation 44de9b57-b6e7-4a46-970d-ebd975ca4f77 · outbound

This paper cites Network dissection: Quantifying interpretability of deep visual representations.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Network dissection: Quantifying interpretability of deep visual representations

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.037866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.488493Z digest=sha256:f6be32a9a20d9ee1fbe83a4ea13609cbdb54e33206378616f7083944e6886fe6

Observation 7b9b8604-2ffd-4926-9ed7-a6d5dfd4f486 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts On the Opportunities and Risks of Foundation Models

Reference 7

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unresolved
no resolver link, observed 2026-08-11T12:35:00.491541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.491541Z digest=sha256:75a02b665255a706c3335b155c0cd34f2f3e66738c9bd238349a80fd486f17ca

Observation 1e7c3b8a-1c37-49f9-ad78-2a021cd85b12 · outbound

This paper cites Contrastive test-time adaptation.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Contrastive test-time adaptation

Reference 8

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unresolved
no resolver link, observed 2026-08-11T12:35:00.494676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.494676Z digest=sha256:0b00564c8c7ecd1dac7cb9ab57d6584a12a6b5592713206b81cab293aa99033f

Observation 5566df84-f262-40fb-9da1-aa41c55c401c · outbound

This paper cites Concept-based explanations for out-of-distribution detectors.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Concept-based explanations for out-of-distribution detectors

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.029335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.497338Z digest=sha256:92ba8962469aa71c32c3b4066dfc3a6c491dff66800853c791605ef768765010

Observation e85c4b01-95fb-4720-9365-73134e4d45ef · outbound

This paper cites Debiasing Vision-Language Models via Biased Prompts.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Debiasing Vision-Language Models via Biased Prompts

Reference 10

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unresolved
no resolver link, observed 2026-08-11T12:35:00.499827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.499827Z digest=sha256:76a8b4c2a17c4cdbb70fb67d747514701df5e4e11810adcdbef7fe1871c8da36

Observation 0bff383b-8355-4249-9b69-451d3d8027ac · outbound

This paper cites an unresolved cited work.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Unresolved cited work

Reference 11

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unresolved
raw_fallback, observed 2026-08-11T12:35:01.020177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.502790Z digest=sha256:701e14a97070f60ef1c2bc4fe99bd6958496773429597431535f44c07c28e5c4

Observation a607a482-6e31-4658-aff9-e0aedde1a661 · outbound

This paper cites Imagebind: One embedding space to bind them all.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Imagebind: One embedding space to bind them all

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:01.012020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.505587Z digest=sha256:b742cce31b769b639e0330ffc0391f9b191150513880fd67314e70f97815783b

Observation 4603e6a7-d386-4821-a56b-2215f1500d79 · outbound

This paper cites Addressing leakage in concept bottleneck models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Addressing leakage in concept bottleneck models

Reference 13

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unresolved
no resolver link, observed 2026-08-11T12:35:00.508173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.508173Z digest=sha256:bae90db11085a6092f3c576202f00772e45878ca420bda0922d6f595c025c7d4

Observation 2d0f0920-c918-4f29-aea7-01cae1e4638b · outbound

This paper cites Benchmarking neural network robustness to common corruptions and perturbations.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Benchmarking neural network robustness to common corruptions and perturbations

Reference 14

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unresolved
no resolver link, observed 2026-08-11T12:35:00.510567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.510567Z digest=sha256:459363f5087a37c2c018f785e1dfa6ace25e284719a2536419ff1a90af74baa3

Observation 1fdbcc77-d61a-414c-bd37-18a28a001c5b · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Scaling up visual and vision-language representation learning with noisy text supervision

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.513163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.513163Z digest=sha256:59050909ad2ee821ffd0a89c84ced66ec683ccaa084bd6ca2c77ca40c3806a90

Observation 97a76b4b-3545-4436-ad55-5901e830f83f · outbound

This paper cites CAFA : Class-aware feature alignment for test-time adaptation.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts CAFA : Class-aware feature alignment for test-time adaptation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.992001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.515722Z digest=sha256:ff060757966169af8964bf02b0592229537f43f8614fdfddc87862e89b7e3610

Observation bb110171-9005-46cd-8116-b24158d96715 · outbound

This paper cites Interpretability beyond feature attribution: Quantitative testing with concept activation vectors ( TCAV ).

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Interpretability beyond feature attribution: Quantitative testing with concept activation vectors ( TCAV )

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.984733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.518282Z digest=sha256:be6a4beae3ced085a402ed9c67981dfca3f2433c0bd845bfcf85cf1abe76eba4

Observation 736825c6-6e86-48c3-88ce-e3f4bde8dadc · outbound

This paper cites Concept bottleneck models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Concept bottleneck models

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.977300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.520968Z digest=sha256:20a3bf4c271b3aca50b02d04f59324960cc1c427b85240d0400277e900d34248

Observation 6f34a32d-1fc2-49f6-9b60-ea8296cd4aea · outbound

This paper cites Fine-tuning can distort pretrained features and underperform out-of-distribution.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Fine-tuning can distort pretrained features and underperform out-of-distribution

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.970163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.523628Z digest=sha256:3d0d16f20a53891183725669bc810704a3a6a486d8ba98be19ad3ba4a6af87ca

Observation 86592c93-8e73-48f4-9f84-8148bc075fe5 · outbound

This paper cites Measure theory, Probability, and Stochastic Processes.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Measure theory, Probability, and Stochastic Processes

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.962308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.526270Z digest=sha256:edc87b134c39200a81954d5010cd8ed54826b75c5b1de8664aead7fbd860606c

Observation 82b26371-cb70-4501-a400-cf4ce966d209 · outbound

This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.954365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.528857Z digest=sha256:67abc2474ef1eabfe4ca53b5a99a92114f5090ef81e3ea524bedb254352de686

Observation c371c02a-5071-4197-b801-88a54f62420f · outbound

This paper cites Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, and Chelsea Finn.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, and Chelsea Finn

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.945803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.531526Z digest=sha256:84c0ff4115949923462d3b17874004fbf38baf3ff52bac6f300fdcf442e02b67

Observation 2761cd94-3664-4127-9d70-2349e15c7f6d · outbound

This paper cites A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts

Reference 23

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no resolver link, observed 2026-08-11T12:35:00.534255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.534255Z digest=sha256:6814b147f5109aeaa47549db980f34dd066efebf1201bb7ad2768bf618a6024d

Observation 0af51bbc-33cf-483f-8928-07d8330b7fb9 · outbound

This paper cites Metashift: A dataset of datasets for evaluating contextual distribution shifts and training conflicts.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Metashift: A dataset of datasets for evaluating contextual distribution shifts and training conflicts

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.937958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.537426Z digest=sha256:53f9ff60706b226b6ad5ab098b35cb4ad149d1a5dfd038ff077ed853a3c6191a

Observation 4e1354ef-d4e2-4f17-b305-fb2a22c75889 · outbound

This paper cites How to exploit hyperspherical embeddings for out-of-distribution detection? In The Eleventh International Conference on Learning Representations ( ICLR ).

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts How to exploit hyperspherical embeddings for out-of-distribution detection? In The Eleventh International Conference on Learning Representations ( ICLR )

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.930082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.539892Z digest=sha256:9f9e1c265c4d851660d8b97c84d7ac1c52e4409285f5fde59e28cfae5522b1ae

Observation 3961f23f-70fe-43ce-82ae-605524ffa60e · outbound

This paper cites Text-to-concept (and back) via cross-model alignment.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Text-to-concept (and back) via cross-model alignment

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.921114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.542339Z digest=sha256:e60def0dbca28524db7a2e025655faced7a21e9ea3eca8a34fa712c800598292

Observation 961e72d5-17e3-49ff-bb56-f983d933888d · outbound

This paper cites Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift

Reference 27

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unresolved
no resolver link, observed 2026-08-11T12:35:00.544923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.544923Z digest=sha256:b57ed4d12b1b71e92086ceaca9c9f66c6b212aead96773972442ffa96aca0c85

Observation 02484436-d867-4092-8d13-2cc36db873c7 · outbound

This paper cites CLIP-Dissect : Automatic description of neuron representations in deep vision networks.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts CLIP-Dissect : Automatic description of neuron representations in deep vision networks

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.912180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.548132Z digest=sha256:4e31d5be5a3dc838b5e80c885f7e5a5865de8cc3a3267ad8df238212eb25307d

Observation ffd7ba51-6426-49b8-a4ee-40b885f40ac9 · outbound

This paper cites Nguyen, and Tsui-Wei Weng.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Nguyen, and Tsui-Wei Weng

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.903629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.550656Z digest=sha256:995f431fca4eb1da96c59c641693ac53dd999d090d842e2514b1e5a5c19da29d

Observation 353cb343-0e07-4647-9165-f8a8d3cabba7 · outbound

This paper cites Dataset shift in machine learning.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Dataset shift in machine learning

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.895000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.553188Z digest=sha256:c303087b9c43156c43a754f94d1c9c956f90815b6e7530623897d80822e1ff86

Observation 49d60300-ccdf-436a-8b42-6dee72c5f771 · outbound

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

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Learning transferable visual models from natural language supervision

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.886415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.555698Z digest=sha256:ac2526f0e46d9fe327687efe51106df3ffd42c0fc76140d370cdde0488961439

Observation 8a368d62-14fd-4af0-a662-206d80fd3271 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts High-resolution image synthesis with latent diffusion models

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.877453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.558255Z digest=sha256:cadf2a32d17a1716a2ab1498e1052179acafdd78669ee2c3a52c4073ec0113ca

Observation 2a4cf413-1777-408f-8a79-b27686b36cb3 · outbound

This paper cites Distributionally robust neural networks.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Distributionally robust neural networks

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.560853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.560853Z digest=sha256:220d8fd0975bd77d468d2d8e7b1888076061f2cf8f809c13d00656cd5e869ff8

Observation 190915d6-c1d5-49c0-b438-2bd8f1f3ff42 · outbound

This paper cites Robust CLIP : Unsupervised adversarial fine-tuning of vision embeddings for robust large vision-language models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Robust CLIP : Unsupervised adversarial fine-tuning of vision embeddings for robust large vision-language models

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.864562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.563406Z digest=sha256:ce3aff5c97cc715402eacae7770d970d3aa8f6f40fcfff44c7c8cb4d44544bb8

Observation f5bcdf7c-2c2a-402f-92a2-e4e6d48ae9ae · outbound

This paper cites Incremental residual concept bottleneck models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Incremental residual concept bottleneck models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.855528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.566041Z digest=sha256:305d553640a704d24248305acafc80122ffc5d1f5280aeb6f948fcbb5e2d893e

Observation acab79f9-368d-44f1-bb85-7ed20de7990c · outbound

This paper cites FixMatch : Simplifying semi-supervised learning with consistency and confidence.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts FixMatch : Simplifying semi-supervised learning with consistency and confidence

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.845917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.568659Z digest=sha256:cd33ea65d56ea863ae07b9c7bd14e4d800c7e88cb495b86c6b640ae304f9e93e

Observation a0735cec-c25e-4f5f-ae13-ae51d27c92bf · outbound

This paper cites Conceptnet 5.5: An open multilingual graph of general knowledge.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Conceptnet 5.5: An open multilingual graph of general knowledge

Reference 37

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no resolver link, observed 2026-08-11T12:35:00.571266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.571266Z digest=sha256:86d8c35a357c43c536bd3a0ddf91d7dfc72dbec7ec604cffb1d784775b925c0b

Observation 80b09267-653c-491f-8530-faead0c7dbc5 · outbound

This paper cites Test-time training with self-supervision for generalization under distribution shifts.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Test-time training with self-supervision for generalization under distribution shifts

Reference 38

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unresolved
no resolver link, observed 2026-08-11T12:35:00.574144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.574144Z digest=sha256:acf83b36460f2c893fb1a727069b0783618326315ef8aae2176a512ecd1b53ec

Observation 4f501c8c-ea4c-4632-b22c-43572812736c · outbound

This paper cites Learning bottleneck concepts in image classification.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Learning bottleneck concepts in image classification

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.827632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.576734Z digest=sha256:0e883cbd473e26bd5b2886d3d21bc5e3ce5bfd91961670aa2c6a9225f6a43f06

Observation e9c47f50-191b-4e36-bce4-61a2099a2d6c · outbound

This paper cites Tent: Fully test-time adaptation by entropy minimization.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Tent: Fully test-time adaptation by entropy minimization

Reference 40

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unresolved
no resolver link, observed 2026-08-11T12:35:00.579173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.579173Z digest=sha256:f8fac68eb33d34b91fd8fc8c0327c9a0e0c4a4f450561070f8f8ba0448d7a33d

Observation c5ee28e0-7c43-463a-80d9-324b121678a4 · outbound

This paper cites MedCLIP: Contrastive Learning from Unpaired Medical Images and Text.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts MedCLIP: Contrastive Learning from Unpaired Medical Images and Text

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.581798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.581798Z digest=sha256:f14c92de7f416c94324350af26b5d866b1771b065a7b5edfc5e8ec947c98d2df

Observation a5f64223-f6d1-443e-957f-32700ba0aba7 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts BloombergGPT: A Large Language Model for Finance

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.584766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.584766Z digest=sha256:e20b90cf72f3d38b9cab2f14b7a9f41f13b95c27a6a88269e12f5d7df4606c81

Observation dfcc7fe5-654d-4ae3-bfec-8e8a6bab8f54 · outbound

This paper cites Discover and Cure: Concept-aware Mitigation of Spurious Correlation.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Discover and Cure: Concept-aware Mitigation of Spurious Correlation

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:35:00.657911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.587746Z digest=sha256:63faa4cbbc4f901819fe094d70406b36d4101304695d2c03dcab5edc1e53f36a

Observation bc166985-d168-4b10-af89-0e4e214cbd0c · outbound

This paper cites Towards a theoretical framework of out-of-distribution generalization.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Towards a theoretical framework of out-of-distribution generalization

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.814239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.590669Z digest=sha256:983fd7998ada36564d3b5acd21817baf0c281c34a7d7f0f13f387c40cf031af1

Observation c77a1494-51fa-404e-aa94-709acb3500ac · outbound

This paper cites On completeness-aware concept-based explanations in deep neural networks.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts On completeness-aware concept-based explanations in deep neural networks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.805976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.593502Z digest=sha256:557e3b24e2336d4f31f0cb1e93ab9a8f85644104f4033e2e134bfbcf74562c23

Observation 5266737c-f9c8-4308-9cfa-e6f89af27ab4 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.797446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.596206Z digest=sha256:4d7bc26d29140cf15e3d46ad14c0bb833e16b44f3c43a605474d0d3abe52cb4c

Observation b9cedf2d-63bb-46c4-b41d-497df794707d · outbound

This paper cites Post-hoc concept bottleneck models.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Post-hoc concept bottleneck models

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.788775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.598861Z digest=sha256:51726a1c64649c298fabc90c763672859ab980463408fbe05f68c23f56b49dc6

Observation c84c0684-3956-46f3-8df8-803ce1f9b43a · outbound

This paper cites MEMO : Test time robustness via adaptation and augmentation.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts MEMO : Test time robustness via adaptation and augmentation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:35:00.780399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-11T12:35:00.601450Z digest=sha256:ed4a169f153ec208b2051b39999f2cc676b4a5e672fa22528b81d9b06aca44af

Observation a12ea3fc-bf50-45f2-9682-e4622e7c284f · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.604205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.604205Z digest=sha256:b7bb99f730b4000578afaa36c60962f3158bcb12e72dc01af8d849df0c8120f8

Observation c240dba7-0fac-4869-9a6e-9acc95f8280a · outbound

This paper cites Regularization and variable selection via the elastic net.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Regularization and variable selection via the elastic net

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.607165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.607165Z digest=sha256:fbcddde33cf78cf1f52f1d55e0f41a4e3f42f217d9dafd06719fdfc136a104b8

Observation bfda1b44-246e-454f-8b29-cd6522cec9e4 · outbound

This paper cites @esa (Ref.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts @esa (Ref

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.609892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.609892Z digest=sha256:039441cac4ccf3c4849ceae48ed6a591b79f0c915cb94e02e0e3ac608d748296

Observation 1f6ff3bc-5faa-4bec-8fa4-cf3e93f01554 · outbound

This paper cites an unresolved cited work.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Unresolved cited work

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.613725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.613725Z digest=sha256:98abc2328daf7b806a6df904e34ddcb547a4f3f90b73d06ddcd9b7be2c3100a8

Observation b4cdc0b2-c74e-46c1-88f1-182590167430 · outbound

This paper cites an unresolved cited work.

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts Unresolved cited work

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:00.616605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:35:00.616605Z digest=sha256:7a2279f44db603476bc9e66379f6e514ab5e03cf31aa0d3b6de6807e5c73a2aa

Pith citing papers

Observation 5e36b8a8-03ba-436f-a086-24266548c043 · inbound

Concept-Based Unsupervised Domain Adaptation cites this paper.

Concept-Based Unsupervised Domain Adaptation Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:03.837201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:17:03.837201Z digest=sha256:ce271f913b86eef0bbc9d69320d4eaad52e1c603ba72f5470c967d5264795778

Observation 2314ef0a-e3f1-4279-9a17-c24fb562498a · inbound

Mitigating Label Bias with Interpretable Rubric Embeddings cites this paper.

Mitigating Label Bias with Interpretable Rubric Embeddings Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:39:41.011548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T05:34:50.412973Z digest=sha256:b4a911af7e15b11b3a36623c852179e442cc182d35bfc6cfc0c26710b72b6666

Observation 3c2ad9e0-01c3-4b63-a11f-aae6ec636a44 · inbound

Multimodal Concept Bottleneck Models cites this paper.

Multimodal Concept Bottleneck Models Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:19:30.859785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T18:12:35.617577Z digest=sha256:5a29909cc917388b1775fb671d284873d10785737f10026a86608e81d693ad32