Paper Citation Record · LEDGER

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning

As of 11 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.05977.

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

pith.paper-citation-record.v1
2506.05977 v1

Coverage vector

measured 40 of 40 reference resolution

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measured 40 of 40 standing notices

One-hop event checks from named stored sources.

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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

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation 8e7989be-275f-4eba-afb3-4cdfd5a77e07 · outbound

This paper cites Bert: Pre- training of deep bidirectional transformers for language under- standing,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Bert: Pre- training of deep bidirectional transformers for language under- standing,

Reference 1

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Observation 6a073708-2e4c-491a-bc7c-bd40cd4ff01b · outbound

This paper cites Lan- guage models are few-shot learners,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Lan- guage models are few-shot learners,

Reference 2

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Observation 6b588d7f-2cc0-4fd1-9418-3e63beed8d31 · outbound

This paper cites Privacy-preserving deep learning,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Privacy-preserving deep learning,

Reference 3

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Observation fca55663-de64-493e-b8c3-5b7e5d46e2d2 · outbound

This paper cites FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks

Reference 4

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Observation 9b42795e-291e-402c-81ba-8abbaa9a1e1d · outbound

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

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Parameter- efficient transfer learning for nlp,

Reference 5

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Observation 89a7bf9b-f8fd-4e85-8206-4f94cdac08d7 · outbound

This paper cites FedAdapter: Efficient Federated Learning for Modern NLP.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning FedAdapter: Efficient Federated Learning for Modern NLP

Reference 6

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Observation 4b0a628f-0c83-4bd0-ad1a-203bb36e1e16 · outbound

This paper cites Fedpetuning: When federated learning meets the parameter- efficient tuning methods of pre-trained language models,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Fedpetuning: When federated learning meets the parameter- efficient tuning methods of pre-trained language models,

Reference 7

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Observation eb8d961e-2ddc-41d8-a4f3-e565eb5492f8 · outbound

This paper cites A continual learn- ing survey: Defying forgetting in classification tasks,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning A continual learn- ing survey: Defying forgetting in classification tasks,

Reference 8

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Observation 5ea4babe-b910-4677-935c-3e6f87449425 · outbound

This paper cites Remind your neural network to prevent catastrophic forgetting,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Remind your neural network to prevent catastrophic forgetting,

Reference 9

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Observation 3ebcd6f0-38e6-4563-ace7-64afaa2034b3 · outbound

This paper cites Rotate your networks: Better weight consoli- dation and less catastrophic forgetting,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Rotate your networks: Better weight consoli- dation and less catastrophic forgetting,

Reference 10

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Observation ded8160d-0d67-42b8-a2ba-6c957ffa208a · outbound

This paper cites Universal statistics of fisher information in deep neural networks: Mean field approach,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Universal statistics of fisher information in deep neural networks: Mean field approach,

Reference 11

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Observation c8c0f7a9-6a56-453f-85f7-aef880161bc1 · outbound

This paper cites Overcoming Forgetting in Federated Learning on Non-IID Data.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Overcoming Forgetting in Federated Learning on Non-IID Data

Reference 12

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Observation 2116c57e-c612-49f0-8795-ba86b3bf6e38 · outbound

This paper cites Federated Learning with Non-IID Data.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Federated Learning with Non-IID Data

Reference 13

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Observation adba4859-13bd-4ec5-a6a3-bb73439f9cc2 · outbound

This paper cites Advances and Open Problems in Federated Learning.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Advances and Open Problems in Federated Learning

Reference 14

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Observation e2c72a2d-3c79-4ae4-862a-0038ff48902d · outbound

This paper cites Fed- erated multi-task learning under a mixture of distributions,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Fed- erated multi-task learning under a mixture of distributions,

Reference 15

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Observation 93d733b5-db75-4118-8e0e-f5c9ae87a175 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 16

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Observation 93329547-11f0-4ce7-b709-9fa372773a61 · outbound

This paper cites Keystrokesniffer: An off-the-shelf smart- phone can eavesdrop on your privacy from anywhere,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Keystrokesniffer: An off-the-shelf smart- phone can eavesdrop on your privacy from anywhere,

Reference 17

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Observation 690f84a7-5171-4871-8036-9acbe11b0ec1 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Communication-efficient learning of deep networks from decentralized data,

Reference 18

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Observation aa5cf4f8-74f8-4510-b600-24c55d6b977e · outbound

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

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Lora: Low-rank adaptation of large language models

Reference 19

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Observation 5d0e08a3-511f-43b8-8cae-6e8fa67abea7 · outbound

This paper cites Feder- ated continual learning via knowledge fusion: A survey,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Feder- ated continual learning via knowledge fusion: A survey,

Reference 20

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Observation aee33326-37ac-472a-9e96-898b35157382 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 21

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Observation 90fd6c84-ddfe-4a3f-ada3-36ee8318e6e2 · outbound

This paper cites Mrpc: Maximizing network lifetime for reliable routing in wireless environments,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Mrpc: Maximizing network lifetime for reliable routing in wireless environments,

Reference 22

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Observation 2cc60a94-7886-4b0b-b371-a5c180a0b30d · outbound

This paper cites The pascal recognising textual entailment challenge,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning The pascal recognising textual entailment challenge,

Reference 23

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This paper cites Recursive deep models for semantic compo- sitionality over a sentiment treebank,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Recursive deep models for semantic compo- sitionality over a sentiment treebank,

Reference 24

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Observation 2a3b7248-61b6-49bd-9f84-f71d314bdd0f · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 25

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This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 26

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This paper cites Finch: Enhancing federated learning with hierarchical neural architecture search,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Finch: Enhancing federated learning with hierarchical neural architecture search,

Reference 27

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Observation 9d2af3fd-6ed9-4981-a7c4-d32749725bf9 · outbound

This paper cites A continual learning survey: Defy- ing forgetting in classification tasks,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning A continual learning survey: Defy- ing forgetting in classification tasks,

Reference 28

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This paper cites Greedy Transition-Based Dependency Parsing with Discrete and Continuous Supertag Features.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Greedy Transition-Based Dependency Parsing with Discrete and Continuous Supertag Features

Reference 29

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Docker: lightweight linux containers for consis- tent development and deployment,

Reference 30

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 31

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Gropp, E

Reference 32

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Observation f57db4d1-6fbe-4756-8eda-15e7d7c738e6 · outbound

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Language models are unsupervised multitask learners,

Reference 33

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning LLaMA: Open and Efficient Foundation Language Models

Reference 34

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Attention is all you need,

Reference 35

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Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Eu general data protection regulation,

Reference 36

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Observation 49b84c43-d161-48f0-9f9b-af49f49bac73 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 37

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This paper cites Adaptive local update and neural composition for accelerating federated learning in heterogeneous edge networks,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Adaptive local update and neural composition for accelerating federated learning in heterogeneous edge networks,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:20:44.666383Z

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Observation ec7708fc-e3db-44c7-931c-8a71dc61a8cc · outbound

This paper cites Enhancing semi-supervised federated learning with progressive training in heterogeneous edge computing,.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning Enhancing semi-supervised federated learning with progressive training in heterogeneous edge computing,

Reference 39

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Observation f3dd5a99-7c92-4c8a-8c42-7393d198d7ce · outbound

This paper cites LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin.

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin

Reference 40

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