Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence | Paper Citation Record

Observation 4e0a7087-bcc0-4b2b-8203-0b86ef389586 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 1

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Observation 79f56404-f2f0-4ebd-aafd-c891f644d0a6 · outbound

This paper cites Improving language understanding by generative pre-training,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Improving language understanding by generative pre-training,

Reference 2

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Observation 078231ff-b815-4419-8ce0-f4dd28a8d524 · outbound

This paper cites Language models are few-shot learners,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Language models are few-shot learners,

Reference 3

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Observation 6a2977ca-3840-4e77-bac4-3d363ee91696 · outbound

This paper cites COMET: Commonsense Transformers for Automatic Knowledge Graph Construction.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

Reference 4

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Observation 0cd2d397-f8df-4c78-b46f-4a58d77e7e41 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Fine-Tuning Language Models from Human Preferences

Reference 5

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

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Parameter-efficient transfer learning for nlp,

Reference 6

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Observation d6c5e5a8-f9ae-4426-a283-146fcab8f47c · outbound

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

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LoRA: Low-rank adaptation of large language models,

Reference 7

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Observation 06c2021e-96b7-4b50-b07b-daea9d9a21ba · outbound

This paper cites Towards a unified view of parameter-efficient transfer learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Towards a unified view of parameter-efficient transfer learning,

Reference 8

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Observation c613ce88-b4d5-47ae-9015-d98bdd675a28 · outbound

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

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence The power of scale for parameter-efficient prompt tuning,

Reference 9

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Observation 5b5d111a-35bb-4948-92d7-3d3dc1b921ec · outbound

This paper cites Prefix-tuning: Optimizing continuous prompts for generation,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Prefix-tuning: Optimizing continuous prompts for generation,

Reference 10

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Observation b1e740bc-5d3c-4c78-9221-67cc839eb6a3 · outbound

This paper cites Residual prompt tuning: improving prompt tuning with residual reparameterization,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Residual prompt tuning: improving prompt tuning with residual reparameterization,

Reference 11

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Observation b2f57976-85c4-4386-9cc0-861a464054d7 · outbound

This paper cites Adaptive budget allocation for parameter-efficient fine- tuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Adaptive budget allocation for parameter-efficient fine- tuning,

Reference 12

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Observation f2202779-1d69-40fa-828f-5f1e8e89cb22 · outbound

This paper cites DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation

Reference 13

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Observation 29f949df-8960-4b21-8b3f-a8334591c684 · outbound

This paper cites IncreLoRA: Incremental Parameter Allocation Method for Parameter-Efficient Fine-tuning.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence IncreLoRA: Incremental Parameter Allocation Method for Parameter-Efficient Fine-tuning

Reference 14

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Observation de6400a7-d2f0-4f7c-9f39-af460740e612 · outbound

This paper cites Dora: Weight-decomposed low-rank adaptation,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Dora: Weight-decomposed low-rank adaptation,

Reference 15

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Observation d5b78b46-802e-43c3-b06a-47973eac256c · outbound

This paper cites Lora+: efficient low rank adaptation of large models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Lora+: efficient low rank adaptation of large models,

Reference 16

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Observation a3e162fb-4ee5-475f-a20c-46227fa720f3 · outbound

This paper cites Vera: Vector-based random matrix adaptation,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Vera: Vector-based random matrix adaptation,

Reference 17

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Observation 63941320-43f5-4db7-9455-b8752eadc724 · outbound

This paper cites Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying

Reference 18

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Observation 8e2f3010-7400-45d6-be70-b059f51e2a07 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Qlora: Efficient finetuning of quantized llms,

Reference 19

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Observation 28de4d86-2c2b-4a60-b88b-a17bbe7a10a6 · outbound

This paper cites QA-loRA: Quantization-aware low-rank adaptation of large language models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence QA-loRA: Quantization-aware low-rank adaptation of large language models,

Reference 20

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Observation 752f0f01-f8d6-4d84-bfe6-5f33013c99c8 · outbound

This paper cites Loftq: LoRA-fine-tuning-aware quantization for large language mod- els,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Loftq: LoRA-fine-tuning-aware quantization for large language mod- els,

Reference 21

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Observation 96f27793-f045-421f-bdc4-99b1652f1b50 · outbound

This paper cites LoRAPrune: Structured pruning meets low-rank parameter-efficient fine-tuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LoRAPrune: Structured pruning meets low-rank parameter-efficient fine-tuning,

Reference 22

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Observation abbdad79-ac6e-4298-83a8-d0393659d362 · outbound

This paper cites NOLA: Compressing loRA using linear combination of random basis,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence NOLA: Compressing loRA using linear combination of random basis,

Reference 23

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This paper cites VB-loRA: Extreme parameter efficient fine- tuning with vector banks,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence VB-loRA: Extreme parameter efficient fine- tuning with vector banks,

Reference 24

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Observation 807fec6d-af6a-4a73-87d3-626713b8bf2b · outbound

This paper cites The impact of initialization on lora finetuning dynamics,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence The impact of initialization on lora finetuning dynamics,

Reference 25

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Observation 7d63506e-f843-499f-b50b-437159d7e42f · outbound

This paper cites LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters

Reference 26

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Observation a76a5d8c-74c8-4af0-8331-784f3399e6cd · outbound

This paper cites Pissa: Principal singular values and singular vectors adaptation of large language models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Pissa: Principal singular values and singular vectors adaptation of large language models,

Reference 27

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Observation 8b1272a1-45fe-4c00-b7ba-a6c3129d238a · outbound

This paper cites Latent retrieval for weakly supervised open domain question answering,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Latent retrieval for weakly supervised open domain question answering,

Reference 28

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Observation cf4443ec-8d61-44b0-a3fa-34d21983a6e3 · outbound

This paper cites TriviaQA: A large scale distantly supervised challenge dataset for reading comprehen- sion,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence TriviaQA: A large scale distantly supervised challenge dataset for reading comprehen- sion,

Reference 29

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This paper cites Metamath: Bootstrap your own mathematical questions for large language models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Metamath: Bootstrap your own mathematical questions for large language models,

Reference 30

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This paper cites Corda: Context-oriented decomposition adaptation of large language models for task-aware parameter-efficient fine-tuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Corda: Context-oriented decomposition adaptation of large language models for task-aware parameter-efficient fine-tuning,

Reference 31

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This paper cites Towards theoretically inspired neural initialization optimization,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Towards theoretically inspired neural initialization optimization,

Reference 32

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Observation 1db21544-2cd0-4497-acd2-1d50a9f1b370 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Training Verifiers to Solve Math Word Problems

Reference 33

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Observation 599a5b93-8a79-4c67-b1da-8ff56df37a76 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Evaluating Large Language Models Trained on Code

Reference 34

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Program Synthesis with Large Language Models

Reference 35

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This paper cites Judging llm-as-a-judge with mt- bench and chatbot arena,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Judging llm-as-a-judge with mt- bench and chatbot arena,

Reference 36

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Observation f36bbe2e-3f9b-4fea-93fb-b751b62710e4 · outbound

This paper cites Semantic parsing on freebase from question-answer pairs,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Semantic parsing on freebase from question-answer pairs,

Reference 37

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence 8-bit optimiz- ers via block-wise quantization,

Reference 38

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Visual instruction tuning,

Reference 39

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Improved baselines with visual instruction tuning,

Reference 40

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence GPT-4 Technical Report

Reference 41

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This paper cites Renaissance: A survey into ai text-to-image generation in the era of large model,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Renaissance: A survey into ai text-to-image generation in the era of large model,

Reference 42

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Galore: Memory-efficient llm training by gradient low-rank projec- tion,

Reference 43

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Observation d99d4a52-9469-4c4a-9871-67aa73ac0cca · outbound

This paper cites Towards interpretable deep local learning with successive gradient reconciliation,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Towards interpretable deep local learning with successive gradient reconciliation,

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Parameter-efficient fine-tuning of large-scale pre-trained language models,

Reference 45

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

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 46

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Conditional adapters: Parameter-efficient transfer learning with fast inference,

Reference 47

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Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Parameter- efficient multi-task fine-tuning for transformers via shared hypernet- works,

Reference 48

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Observation b308ec1f-3b87-4324-8f80-6cce7d6b255e · outbound

This paper cites Adapter- fusion: Non-destructive task composition for transfer learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Adapter- fusion: Non-destructive task composition for transfer learning,

Reference 49

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This paper cites Compacter: Ef- ficient low-rank hypercomplex adapter layers,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Compacter: Ef- ficient low-rank hypercomplex adapter layers,

Reference 50

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Observation fc840a86-b389-4978-9452-a3ce5b62694f · outbound

This paper cites SPT: Learning to selectively insert prompts for better prompt tuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence SPT: Learning to selectively insert prompts for better prompt tuning,

Reference 51

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Observation 598468e7-7a14-429f-9b03-2f1120acd109 · outbound

This paper cites Measuring the intrinsic dimension of objective landscapes,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Measuring the intrinsic dimension of objective landscapes,

Reference 52

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This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

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Observation e23c0c18-8c86-4e49-aca5-d78808f26ce8 · outbound

This paper cites One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning

Reference 54

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This paper cites Controlling text-to-image diffusion by orthogonal finetuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Controlling text-to-image diffusion by orthogonal finetuning,

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:08.484502Z

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Observation b47ea63a-1d5f-443c-b30b-e31dd18b5807 · outbound

This paper cites LQ-loRA: Low-rank plus quantized matrix decomposition for efficient language model finetuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LQ-loRA: Low-rank plus quantized matrix decomposition for efficient language model finetuning,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:08.178882Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5bdf4043-ac58-4559-abf6-d6b2ca1018a1 · outbound

This paper cites When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:49.397014Z

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Observation 2e5cc9b6-1a07-43ca-8599-e6d67a76d7e1 · outbound

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

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:49.467029Z

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Observation eda3c0dd-bf0b-47b8-bf5a-cd10c8eb27d5 · outbound

This paper cites MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:49.601007Z

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Observation 03cde7a9-0cf9-46f2-a7ab-89da80c5df7f · outbound

This paper cites Awq: Activation-aware weight quanti- zation for llm compression and acceleration,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Awq: Activation-aware weight quanti- zation for llm compression and acceleration,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:07.805437Z

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Observation a04e5bdb-bc39-4688-ab60-6b098d39b26d · outbound

This paper cites ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:49.873768Z

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Observation 8b07358b-176a-4838-b29d-fe5e53fe0728 · outbound

This paper cites Owq: Outlier-aware weight quantization for efficient fine-tuning and inference of large language models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Owq: Outlier-aware weight quantization for efficient fine-tuning and inference of large language models,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:07.535099Z

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Observation d01f5ad9-2c8a-48a6-9f1b-c39504544701 · outbound

This paper cites An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:50.102023Z

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Observation 87027867-d6a8-425c-8508-c9b18e59dadf · outbound

This paper cites icarl: Incremental classifier and representation learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence icarl: Incremental classifier and representation learning,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:07.221333Z

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Observation 6b665f51-91bf-4960-8c86-3c38aacf6644 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Overcoming catastrophic forgetting in neural networks,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:50.319220Z

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Observation ee3f5f4b-82f3-4791-941e-3d56b7576207 · outbound

This paper cites Continual unsupervised representation learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Continual unsupervised representation learning,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:06.916826Z

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Observation 134abdc0-dac7-4e01-88bc-3b5265753b42 · outbound

This paper cites Gradient episodic memory for contin- ual learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Gradient episodic memory for contin- ual learning,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:06.588358Z

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Observation 280d89fe-59c3-4d26-9f59-0120837c0f9c · outbound

This paper cites Neural collapse inspired feature-classifier alignment for few-shot class incremental learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Neural collapse inspired feature-classifier alignment for few-shot class incremental learning,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:06.249090Z

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Observation 923929a5-82ee-41d7-a95f-7c29e9c8ddf4 · outbound

This paper cites Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:43:56.790321Z

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Observation a823e471-a185-4420-b858-6d67bb28161c · outbound

This paper cites Enhancing online continual learning with plug-and-play state space model and class-conditional mixture of discretization,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Enhancing online continual learning with plug-and-play state space model and class-conditional mixture of discretization,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:05.961176Z

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Observation e50ad91a-f484-4ec4-9c77-3cc13776029c · outbound

This paper cites Learning without forgetting,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Learning without forgetting,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:05.683857Z

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Observation 3840cfc6-1e3d-4eee-945c-062d2cf48c7b · outbound

This paper cites Learning a unified classifier incrementally via rebalancing,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Learning a unified classifier incrementally via rebalancing,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:05.436484Z

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Observation 5854041b-f440-441f-81d0-210f7f0c49f9 · outbound

This paper cites Learning to learn without forgetting by maximizing transfer and minimizing interference,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Learning to learn without forgetting by maximizing transfer and minimizing interference,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:05.104704Z

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Observation c88400c1-3b00-426a-89be-3423fa2745d5 · outbound

This paper cites Der: Dynamically expandable representation for class incremental learning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Der: Dynamically expandable representation for class incremental learning,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:04.843100Z

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Observation 10af06ab-1c71-4686-9b39-c95862ac5a4d · outbound

This paper cites Continual Learning for Large Language Models: A Survey.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Continual Learning for Large Language Models: A Survey

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:51.513729Z

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Observation e2b33d26-f614-4f2f-88d2-49433c214497 · outbound

This paper cites Continual Instruction Tuning for Large Multimodal Models.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Continual Instruction Tuning for Large Multimodal Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:51.674160Z

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Observation 3b54e5bd-307d-4093-99c8-e7e7d3168f98 · outbound

This paper cites Investi- gating the catastrophic forgetting in multimodal large language model fine-tuning,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Investi- gating the catastrophic forgetting in multimodal large language model fine-tuning,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:04.551931Z

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Observation eb028ab5-6cda-46f2-a0f3-5d15df05cc09 · outbound

This paper cites Fine-tuned language models are continual learners,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Fine-tuned language models are continual learners,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:04.279934Z

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Observation af4c1015-42a6-40e1-bf9a-deff4a36f8bf · outbound

This paper cites Continual pre-training of large language models: How to re-warm your model?.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Continual pre-training of large language models: How to re-warm your model?

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:03.980770Z

Source-reported events for the cited work

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Observation 07dc000e-6f66-4c22-ae45-3bb023404480 · outbound

This paper cites Simple and Scalable Strategies to Continually Pre-train Large Language Models.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Simple and Scalable Strategies to Continually Pre-train Large Language Models

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:52.260130Z

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Observation b573473a-ce02-49e1-b873-e91e21ac2724 · outbound

This paper cites LLaMA Pro: Progressive LLaMA with Block Expansion.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence LLaMA Pro: Progressive LLaMA with Block Expansion

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:52.400027Z

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Observation 52b5eab1-6738-49f9-a552-ba9669285cce · outbound

This paper cites Composing parameter-efficient modules with arithmetic operation,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Composing parameter-efficient modules with arithmetic operation,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:03.673889Z

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Observation a8e9b597-3d99-4a93-94ba-d5d62d14038b · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Language models are super mario: Absorbing abilities from homologous models as a free lunch,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:03.376211Z

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Observation f788424e-5026-405a-956c-ce29412f4424 · outbound

This paper cites Model tailor: Mitigating catastrophic forgetting in multi-modal large language models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Model tailor: Mitigating catastrophic forgetting in multi-modal large language models,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:03.050389Z

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Observation 801abad0-1370-4dec-bda5-62e6a5d74dbb · outbound

This paper cites Language model compression with weighted low-rank factorization,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Language model compression with weighted low-rank factorization,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:02.793373Z

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Observation 73cf7f4b-9073-4ad7-b512-a9e32ebef77a · outbound

This paper cites SVD-LLM: Truncation- aware singular value decomposition for large language model compres- sion,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence SVD-LLM: Truncation- aware singular value decomposition for large language model compres- sion,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:02.459725Z

Source-reported events for the cited work

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Observation c418a7bf-e8f0-454b-a482-cf80ceabed3d · outbound

This paper cites Optimizing Singular Spectrum for Large Language Model Compression.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Optimizing Singular Spectrum for Large Language Model Compression

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:53.000581Z

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Observation db661954-551f-4a82-a752-2519b7e7a25d · outbound

This paper cites Exploring post-training quantization in llms from comprehensive study to low rank compensa- tion,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Exploring post-training quantization in llms from comprehensive study to low rank compensa- tion,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:02.172522Z

Source-reported events for the cited work

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Observation b72617bb-fbf8-479a-8199-33daa7d48306 · outbound

This paper cites SVDQuant: Absorbing outliers by low-rank component for 4-bit diffusion models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence SVDQuant: Absorbing outliers by low-rank component for 4-bit diffusion models,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:01.881213Z

Source-reported events for the cited work

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Observation dd930b33-efde-4281-900b-43e9ec7b923d · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:53.440903Z

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Observation 4069392f-eeff-48b6-a2de-8825e37f2205 · outbound

This paper cites Pointer Sentinel Mixture Models.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Pointer Sentinel Mixture Models

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:53.564627Z

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Observation 27ffa1e0-0fb4-4701-a2c8-176b54787184 · outbound

This paper cites Building a large annotated corpus of english: The penn treebank,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Building a large annotated corpus of english: The penn treebank,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:01.647561Z

Source-reported events for the cited work

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Observation 7fa2b942-2726-43d3-919e-e0f6e64417b6 · outbound

This paper cites Natural questions: a benchmark for question answering research,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Natural questions: a benchmark for question answering research,

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:53.752677Z

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Observation 239d11d4-a6c8-4c2c-b2e8-a4f8908f0264 · outbound

This paper cites Gpt3.int8(): 8-bit matrix multiplication for transformers at scale,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Gpt3.int8(): 8-bit matrix multiplication for transformers at scale,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:01.393482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 09b2abaa-5599-4420-a901-ce510db742a2 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Smoothquant: Accurate and efficient post-training quantization for large language models,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:01.079579Z

Source-reported events for the cited work

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Observation 9c0de6f7-a178-4468-93e9-64621ff76a27 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:54.091090Z

Source-reported events for the cited work

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Observation c5352022-b6c0-494d-b56d-2096def99028 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Gemma 2: Improving Open Language Models at a Practical Size

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:54.146385Z

Source-reported events for the cited work

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Observation 548cae34-c6b5-4ab7-ae0c-881582be1418 · outbound

This paper cites OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:54.234553Z

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Observation 2a149dba-c1df-4c25-811c-62b3e5a3f958 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence WizardLM: Empowering large pre-trained language models to follow complex instructions,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:00.759259Z

Source-reported events for the cited work

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Observation a69e3f49-909e-4dcc-95fa-285996447255 · outbound

This paper cites Judging LLM-as-a-judge with MT-bench and chatbot arena,.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Judging LLM-as-a-judge with MT-bench and chatbot arena,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:00.445069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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