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Paper Citation Record · LEDGER

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning

As of 22 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2505.05062.

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

pith.paper-citation-record.v1
2505.05062 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:17:53.759604Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

49 of 49 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 320622f4-a556-4585-9525-6dbd322d16a9 · outbound

This paper cites Dash: Semi-supervised learning with dynamic thresholding,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Dash: Semi-supervised learning with dynamic thresholding,

Reference 1

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Observation 4e2fe0fd-c380-4754-87e3-8668049e2c26 · outbound

This paper cites Cossl: Co-learning of representation and classifier for imbalanced semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Cossl: Co-learning of representation and classifier for imbalanced semi-supervised learning,

Reference 2

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Observation 148d9a42-a2fd-4929-9597-9648ebf8348f · outbound

This paper cites FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Reference 3

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Observation d35073c0-6033-4354-85d4-db15633e4ac5 · outbound

This paper cites AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning

Reference 4

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Observation 4651e668-6a1d-49d6-a5de-42eb4e632a01 · outbound

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

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Fixmatch: Simplifying semi- supervised learning with consistency and confidence,

Reference 5

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Observation 27612773-a133-4743-b547-780b4f4c6a82 · outbound

This paper cites Dynamic learnable logit adjustment for long-tailed visual recognition,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Dynamic learnable logit adjustment for long-tailed visual recognition,

Reference 6

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Observation d2a7ff3d-be4c-4325-b815-8facb7a2b314 · outbound

This paper cites Learning label shift correction for test-agnostic long-tailed recognition,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Learning label shift correction for test-agnostic long-tailed recognition,

Reference 7

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Source-reported events for the cited work

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Observation 6c04082b-fa83-4216-9333-8ede1653f3de · outbound

This paper cites Large- scale long-tailed recognition in an open world,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Large- scale long-tailed recognition in an open world,

Reference 8

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Source-reported events for the cited work

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Observation 947e70b6-653a-4154-b082-92673fcba73f · outbound

This paper cites Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition

Reference 9

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Source-reported events for the cited work

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Observation 231f92aa-0c87-4634-b25e-b99e31c89cb3 · outbound

This paper cites Towards realistic long-tailed semi-supervised learning: Consistency is all you need,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Towards realistic long-tailed semi-supervised learning: Consistency is all you need,

Reference 10

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Observation 7e595e7f-717e-4e56-8918-f30636a95034 · outbound

This paper cites Three heads are better than one: Complementary experts for long-tailed semi-supervised learn- ing,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Three heads are better than one: Complementary experts for long-tailed semi-supervised learn- ing,

Reference 11

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Source-reported events for the cited work

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Observation 399d19e9-0e7b-494e-946c-882472a5e987 · outbound

This paper cites Distribu- tion aligning refinery of pseudo-label for imbalanced semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Distribu- tion aligning refinery of pseudo-label for imbalanced semi-supervised learning,

Reference 12

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Source-reported events for the cited work

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Observation 5f50bb5b-6d19-4bb2-aacb-dad99a1d93a1 · outbound

This paper cites Crest: A class- rebalancing self-training framework for imbalanced semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Crest: A class- rebalancing self-training framework for imbalanced semi-supervised learning,

Reference 13

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Source-reported events for the cited work

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Observation 1012b6df-6f3e-49f8-8618-5bed4d2060d1 · outbound

This paper cites Class-imbalanced semi-supervised learning with adaptive thresholding,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Class-imbalanced semi-supervised learning with adaptive thresholding,

Reference 14

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Source-reported events for the cited work

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Observation f4eee876-4bf0-4d7a-a421-d5d22e20e4c8 · outbound

This paper cites Smoothed adaptive weighting for imbalanced semi-supervised learning: Improve reliability against unknown distribution data,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Smoothed adaptive weighting for imbalanced semi-supervised learning: Improve reliability against unknown distribution data,

Reference 15

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Source-reported events for the cited work

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Observation d98c88c8-7a94-4e61-8d0c-5db70fd252b9 · outbound

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

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Learning transferable visual models from natural language supervision,

Reference 16

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Observation f94030af-5f50-4540-9f8d-6d5b28b17a6b · outbound

This paper cites What makes clip more robust to long-tailed pre-training data? a controlled study for transferable insights,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning What makes clip more robust to long-tailed pre-training data? a controlled study for transferable insights,

Reference 17

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Observation e394cc45-0b86-48bf-912c-ff38469dcc78 · outbound

This paper cites Long-tail learning with foundation model: Heavy fine-tuning hurts,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Long-tail learning with foundation model: Heavy fine-tuning hurts,

Reference 18

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Source-reported events for the cited work

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Observation 8477b09e-9b60-4dd7-9a8f-29451fd8f2fd · outbound

This paper cites Learning transferable negative prompts for out-of-distribution detection,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Learning transferable negative prompts for out-of-distribution detection,

Reference 19

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Observation 33288d26-4b27-4c1d-ab2b-01d93ba64512 · outbound

This paper cites Locoop: Few-shot out- of-distribution detection via prompt learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Locoop: Few-shot out- of-distribution detection via prompt learning,

Reference 20

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Observation da58db23-36e6-4569-af90-f34c945dbe00 · outbound

This paper cites Daso: Distribution-aware semantics- oriented pseudo-label for imbalanced semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Daso: Distribution-aware semantics- oriented pseudo-label for imbalanced semi-supervised learning,

Reference 21

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Observation a52c881a-c431-462d-a2fd-ea20bc96abb9 · outbound

This paper cites Bacon: Boosting imbalanced semi- supervised learning via balanced feature-level contrastive learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Bacon: Boosting imbalanced semi- supervised learning via balanced feature-level contrastive learning,

Reference 22

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Observation 2306e604-7f4f-4894-86bb-ada28d5995cb · outbound

This paper cites Abc: Auxiliary balanced classifier for class-imbalanced semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Abc: Auxiliary balanced classifier for class-imbalanced semi-supervised learning,

Reference 23

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Observation 9667253d-1837-4591-af9e-ee218347fd12 · outbound

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

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 24

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Observation af6fbf33-099c-4859-9ac3-7d9e6f27dae6 · outbound

This paper cites Slip: Self-supervision meets language-image pre-training,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Slip: Self-supervision meets language-image pre-training,

Reference 25

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Observation d15ac2e6-6709-4998-b8eb-c9d7cf563204 · outbound

This paper cites Coca: Contrastive captioners are image-text foundation models,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Coca: Contrastive captioners are image-text foundation models,

Reference 26

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Observation 7a70b7a4-9f90-4c71-a775-567669f16683 · outbound

This paper cites SimVLM: Simple Visual Language Model Pretraining with Weak Supervision.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning SimVLM: Simple Visual Language Model Pretraining with Weak Supervision

Reference 27

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Observation 7ade4397-dcbb-459c-805d-df02613b46ce · outbound

This paper cites Uniformly distributed cat- egory prototype-guided vision-language framework for long-tail recog- nition,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Uniformly distributed cat- egory prototype-guided vision-language framework for long-tail recog- nition,

Reference 28

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Observation 483fba16-b21e-4fba-94b0-09c3eaeca487 · outbound

This paper cites Vl-ltr: Learning class- wise visual-linguistic representation for long-tailed visual recognition,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Vl-ltr: Learning class- wise visual-linguistic representation for long-tailed visual recognition,

Reference 29

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Observation 1b301e7c-39ca-467e-be14-9864907f0154 · outbound

This paper cites Ltgc: Long- tail recognition via leveraging llms-driven generated content,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Ltgc: Long- tail recognition via leveraging llms-driven generated content,

Reference 30

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Source-reported events for the cited work

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Observation e1ef1660-23f1-403e-b956-7c9bfc314e87 · outbound

This paper cites A Simple Long-Tailed Recognition Baseline via Vision-Language Model.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning A Simple Long-Tailed Recognition Baseline via Vision-Language Model

Reference 31

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Observation 90082658-30a8-42e0-95e6-1e9f0dbb3223 · outbound

This paper cites Lpt: Long-tailed prompt tuning for image classification,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Lpt: Long-tailed prompt tuning for image classification,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 754bc780-665c-4d8a-a7b8-b1272426e144 · outbound

This paper cites Improving visual prompt tuning by gaussian neighborhood minimization for long- tailed visual recognition,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Improving visual prompt tuning by gaussian neighborhood minimization for long- tailed visual recognition,

Reference 33

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raw_fallback, observed 2026-08-15T23:17:54.183300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.681987Z digest=sha256:140a6e4c7750fccaef762ebcff4b7cafdcb09c6e30250d4850ebd231501aa396

Observation f9b8bc17-a308-4810-a1e9-2e57bfcb926e · outbound

This paper cites Imbalanced semi- supervised learning with bias adaptive classifier,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Imbalanced semi- supervised learning with bias adaptive classifier,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.167913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.686924Z digest=sha256:68c6954eb4bf4e7997229695f5514b8f8fde361fe0c36d456e1c6b00f460cc5e

Observation daf68f57-d5f9-44c2-b491-1d8d6918d143 · outbound

This paper cites Bem: Balanced and entropy-based mix for long-tailed semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Bem: Balanced and entropy-based mix for long-tailed semi-supervised learning,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.151825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.692545Z digest=sha256:24c1b4e9e383eaf6f501c9cf961ec8a7132515ac595dbfd723c1a311e844d584

Observation 360b4785-b3e3-4274-871a-406e69325c6a · outbound

This paper cites Twice class bias correction for imbalanced semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Twice class bias correction for imbalanced semi-supervised learning,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.135756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.698152Z digest=sha256:c05f9e7ed569d6c0e586bb037d02aafde22ab5f9a58cd29889416826e492fc71

Observation b57d4a76-d335-423f-b722-547d1db07847 · outbound

This paper cites Continuous contrastive learning for long-tailed semi-supervised recog- nition,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Continuous contrastive learning for long-tailed semi-supervised recog- nition,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.120090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.702991Z digest=sha256:19e80cade8eb129999a2097836c4c969b09d1d573dbd11275a29474f259c3992

Observation 7fb272c1-e75f-44c5-8d44-47359ac82ca9 · outbound

This paper cites Long-tail learning via logit adjustment.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Long-tail learning via logit adjustment

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.708179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.708179Z digest=sha256:2af4eea052918bab60e0af631edb7bbc3714ed6fb6ce98da1f28136d1a1094e5

Observation a8f4e5e5-d539-4334-baa1-6cebcc4baea9 · outbound

This paper cites Learning multiple layers of features from tiny images,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Learning multiple layers of features from tiny images,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.713416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.713416Z digest=sha256:61575e8275a2993449f11ed3cbe9e462dcba2533bef823f70516b208c41176f4

Observation 003bb793-0535-44dd-94d7-f6b74cc255fd · outbound

This paper cites An analysis of single-layer networks in unsupervised feature learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning An analysis of single-layer networks in unsupervised feature learning,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.717890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.717890Z digest=sha256:bf5b4aaf08ffba8761510a452a3f7eb0bf33eaa6bc9995ba08e79ecb40795f73

Observation 76b189d4-3dd5-4603-816a-5b48f664c379 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Pytorch: An imperative style, high-performance deep learning library,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.722603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.722603Z digest=sha256:190f785d438a92cbd1b8e70b5dae67fbded28404698c24142b0f4f679c80d535

Observation bef38047-7711-48a9-baa5-178348021e11 · outbound

This paper cites Erasing the bias: Fine-tuning foundation models for semi-supervised learning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Erasing the bias: Fine-tuning foundation models for semi-supervised learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.071204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.727423Z digest=sha256:9de170c8cb5933fe932e7c0afc76064e3f762e9d0fc7050284d8af3d00cac0ce

Observation 08659c90-a6b6-4563-994b-061d70ed54e2 · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recogni- tion,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Adaptformer: Adapting vision transformers for scalable visual recogni- tion,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.732132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.732132Z digest=sha256:995cb3bb11cd6dbff98eaeb6fab77a0ba565afac7ed8c0bb45a3a4a3c3525237

Observation 2c9b1112-73ed-4805-88eb-9bdbfc079a33 · outbound

This paper cites Transfer and share: semi-supervised learning from long-tailed data,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Transfer and share: semi-supervised learning from long-tailed data,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.045741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.736858Z digest=sha256:79d6ea9690731beaa1a59103f63a07f21010bfcf6c50ceb87fa6d68e6c42d270

Observation 35bbbb64-3fba-4a44-804d-164eaab4c15e · outbound

This paper cites Debiased learning from naturally imbalanced pseudo-labels,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Debiased learning from naturally imbalanced pseudo-labels,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:54.029866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.741234Z digest=sha256:3b4bcaed4935bcb3d86d5d73ca72744b9231f6f388debeb8a579bcda4841f8e9

Observation 2f4bf971-8de1-42ef-8f49-018a23bc6dae · outbound

This paper cites Bitfit: Simple parameter- efficient fine-tuning for transformer-based masked language-models,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Bitfit: Simple parameter- efficient fine-tuning for transformer-based masked language-models,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.746103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.746103Z digest=sha256:dd4fc3340eac0ac34169638b4a3a55a4601796b11329a868fd18bafb3d9322d0

Observation fa3e70fa-bdb4-4beb-a1be-727f77f16fca · outbound

This paper cites Visual prompt tuning,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Visual prompt tuning,

Reference 47

Resolution
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no resolver link, observed 2026-08-15T23:17:53.750805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.750805Z digest=sha256:3bc61e31caa6326c2405b5c5c76ba3da9e37dc993a60d70870c98e4ff4cecd3d

Observation 821f4438-bb84-4781-a6c4-d0e598c2ab37 · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Parameter-efficient transfer learning for nlp,

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T23:17:53.755246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:17:53.755246Z digest=sha256:0cba53ad0f4a25f1b29fe78b8420009f6b1e294e506ce49d7231ccd1f64a0e49

Observation ddefaf09-2f57-4b40-8a14-b19e501b2643 · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning Lora: Low-rank adaptation of large language models,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:17:53.991248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T23:17:53.759604Z digest=sha256:2ca5b9628611c0652501c12ecbb0e288055f761f9769d954be202214751d7616

Pith citing papers

No inbound Pith citation observations are available.