GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning | Paper Citation Record

Observation aaf4e3bc-b302-44ce-8ff0-90b97b8340a5 · outbound

This paper cites Online Continual Learning with Maximally Interfered Retrieval.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Online Continual Learning with Maximally Interfered Retrieval

Reference 1

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Observation 7abaae1b-7e97-403c-9dfb-79c21248690c · outbound

This paper cites Gradient based sample selection for online continual learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Gradient based sample selection for online continual learning

Reference 2

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Observation 3de7c274-7350-4da9-90e9-8085b9943cda · outbound

This paper cites Rainbow memory: Continual learning with a memory of diverse samples.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Rainbow memory: Continual learning with a memory of diverse samples

Reference 3

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This paper cites Selecting representative data sets.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Selecting representative data sets

Reference 4

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Observation 922c372d-0e75-44f0-aa12-0934ad6ed8a0 · outbound

This paper cites Dokania, Thalaiyasingam Ajanthan, and Philip H.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Dokania, Thalaiyasingam Ajanthan, and Philip H

Reference 5

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Observation 68e4af7f-4cfa-4526-a7fc-fb10a733857f · outbound

This paper cites Efficient Lifelong Learning with A-GEM.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Efficient Lifelong Learning with A-GEM

Reference 6

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Observation f9ef4a1b-f78c-4ce9-8f7d-26367ff795f4 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Scaling Instruction-Finetuned Language Models

Reference 7

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Observation 65d0145c-2b28-4196-8fa0-dfa74b61f5b7 · outbound

This paper cites Episodic memory in lifelong language learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Episodic memory in lifelong language learning

Reference 8

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Observation f76dd274-6bb3-4c58-b4dc-35cf032225c8 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Parameter-efficient fine-tuning of large-scale pre-trained language models

Reference 9

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Observation 5088cccb-8157-447f-bbbb-9b9af8fbcccd · outbound

This paper cites Dytox: Transformers for continual learning with dynamic token expansion.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Dytox: Transformers for continual learning with dynamic token expansion

Reference 10

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Observation 6ad11870-723e-4524-b831-e8753f885ec1 · outbound

This paper cites Memory efficient continual learning with transformers.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Memory efficient continual learning with transformers

Reference 11

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Observation ded21617-762f-4eab-9429-142acbf17f72 · outbound

This paper cites PPT: Pre-trained Prompt Tuning for Few-shot Learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 12

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Observation 88cace18-6d4b-4c83-90f6-706222e90a37 · outbound

This paper cites Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning

Reference 13

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This paper cites Visual prompt tuning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Visual prompt tuning

Reference 14

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Observation f0199218-1147-4b99-bdf4-2a43ca774d55 · outbound

This paper cites Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt

Reference 15

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Observation 15fe70e1-9b0a-42c3-b6a3-5c3bd9d7ee43 · outbound

This paper cites GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 16

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Observation 4fc4fa79-4d77-4a4f-aa99-c1ad2de686e8 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Overcoming catastrophic forgetting in neural networks

Reference 17

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Observation 6253a496-05e4-4961-a081-ce156931f108 · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning The power of scale for parameter-efficient prompt tuning

Reference 18

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This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 19

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Observation 29aaeb2f-1116-4e69-9253-92c96fce5ad3 · outbound

This paper cites Learning without forgetting.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Learning without forgetting

Reference 20

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Observation e49a8577-7c4a-4675-b617-080eecbd5b42 · outbound

This paper cites Learning word vectors for sentiment analysis.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Learning word vectors for sentiment analysis

Reference 21

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Observation a0d233de-48f6-44dc-83ed-a13701d33c10 · outbound

This paper cites Catastrophic interference in connectionist networks: The sequential learning problem.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Catastrophic interference in connectionist networks: The sequential learning problem

Reference 22

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This paper cites Coresets for Data-efficient Training of Machine Learning Models.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Coresets for Data-efficient Training of Machine Learning Models

Reference 23

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This paper cites Q.: A survey on transfer learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Q.: A survey on transfer learning

Reference 24

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Observation 4bae5a01-cabc-4a11-8e98-c41d05008357 · outbound

This paper cites LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5

Reference 25

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Observation a97a4305-72e3-428d-bfb9-585b04106c88 · outbound

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

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 26

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This paper cites Progressive prompts: Continual learning for language models.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Progressive prompts: Continual learning for language models

Reference 27

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This paper cites icarl: Incremental classifier and representation learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning icarl: Incremental classifier and representation learning

Reference 28

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Observation 83eeef6a-16ef-481e-9dcf-f060fd032a10 · outbound

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

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 29

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This paper cites Representation matters: Assessing the importance of subgroup allocations in training data.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Representation matters: Assessing the importance of subgroup allocations in training data

Reference 30

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This paper cites AdapterDrop : O n the efficiency of adapters in transformers.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning AdapterDrop : O n the efficiency of adapters in transformers

Reference 31

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This paper cites Progressive Neural Networks.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Progressive Neural Networks

Reference 32

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GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Unresolved cited work

Reference 33

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This paper cites Continual learning with deep generative replay.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Continual learning with deep generative replay

Reference 34

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This paper cites Coda-prompt: Continual decomposed attention-based prompting for rehearsal-free continual learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Coda-prompt: Continual decomposed attention-based prompting for rehearsal-free continual learning

Reference 35

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This paper cites LAMOL: LAnguage MOdeling for Lifelong Language Learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning LAMOL: LAnguage MOdeling for Lifelong Language Learning

Reference 36

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This paper cites Three scenarios for continual learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Three scenarios for continual learning

Reference 37

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This paper cites Efficient Continual Learning with Modular Networks and Task-Driven Priors.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Efficient Continual Learning with Modular Networks and Task-Driven Priors

Reference 38

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This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 39

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This paper cites Superglue: A stickier benchmark for general-purpose language understanding systems.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Superglue: A stickier benchmark for general-purpose language understanding systems

Reference 40

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This paper cites Pre-trained language models and their applications.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Pre-trained language models and their applications

Reference 41

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This paper cites A comprehensive survey of continual learning: Theory, method and application.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning A comprehensive survey of continual learning: Theory, method and application

Reference 42

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This paper cites Multitask prompt tuning enables parameter-efficient transfer learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Multitask prompt tuning enables parameter-efficient transfer learning

Reference 43

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This paper cites Dualprompt: Complementary prompting for rehearsal-free continual learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Dualprompt: Complementary prompting for rehearsal-free continual learning

Reference 44

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This paper cites Learning to prompt for continual learning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Learning to prompt for continual learning

Reference 45

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This paper cites Efficient meta lifelong-learning with limited memory.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Efficient meta lifelong-learning with limited memory

Reference 46

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This paper cites Mitigate negative transfer with similarity heuristic lifelong prompt tuning.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Mitigate negative transfer with similarity heuristic lifelong prompt tuning

Reference 47

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This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 48

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This paper cites C on T in T in: Continual learning from task instructions.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning C on T in T in: Continual learning from task instructions

Reference 49

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This paper cites Lifelong learning with dynamically expandable networks.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Lifelong learning with dynamically expandable networks

Reference 50

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This paper cites Continual learning through synaptic intelligence.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Continual learning through synaptic intelligence

Reference 51

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This paper cites Character-level convolutional networks for text classification.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Character-level convolutional networks for text classification

Reference 52

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This paper cites Continual prompt tuning for dialog state tracking.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Continual prompt tuning for dialog state tracking

Reference 53

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This paper cites write newline.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning write newline

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