Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:16.082796Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 2 inbound Pith citation observations for arXiv:2506.00495.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:16.082796Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T09:01:46.458539Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T18:51:07.429970Z
52 of 52 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7683bbbb-542d-4a21-99f3-248b5425294d · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Optuna: A next- generation hyperparameter optimization framework
Reference 1
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Observation 0ad25361-6050-4fc0-9571-b5c1b08b8c91 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Lawyer-instruct, 2024
Reference 2
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1ef382ed-9a9a-40cb-b28a-92d33167cddd · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c6c3ea2a-3dc2-47b0-84d3-79e2ede3326e · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Code alpaca: An instruction-following llama model for code generation
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b66aaec8-d160-43ba-bfb3-e2c5a3e8e6e6 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Evaluating Large Language Models Trained on Code
Reference 5
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Observation 2d0ef40b-9c6f-4ca2-9015-ee2215dd5902 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Reference 6
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Unavailable: canonical work link unavailable.
Observation c09ad824-72cd-46f1-aca0-212920c393dc · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Training Verifiers to Solve Math Word Problems
Reference 7
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Unavailable: canonical work link unavailable.
Observation ea3c9c56-9ebb-4ecf-9443-872ff52aae0f · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Sparse Low-rank Adaptation of Pre-trained Language Models
Reference 8
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Observation 82c30370-8b25-41b2-81ec-59f267d1155f · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin
Reference 9
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Observation 0113ec4d-12cc-47a3-a9ee-8541f257414a · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding
Reference 10
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Observation 13e82321-11c0-4552-aca1-724394c2d4d1 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Sparsegpt: Massive language models can be accurately pruned in one-shot
Reference 11
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 99355fc6-1aec-49fa-933d-c834be2ef5b3 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts MoLA: MoE LoRA with layer-wise expert allocation
Reference 12
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a7539167-998f-4850-97f6-2d71c6791861 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LoRA+: Efficient Low Rank Adaptation of Large Models
Reference 13
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Unavailable: canonical work link unavailable.
Observation 35191f7c-ee29-4acb-b4d7-5ac735ccebf7 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Measuring Massive Multitask Language Understanding
Reference 14
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Observation 65d3186f-8a03-4440-a8e6-a798f8ac1388 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LoRA: Low-Rank Adaptation of Large Language Models
Reference 15
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Observation 59efa1c4-7256-4603-85e4-1dddbf36c5c0 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition
Reference 16
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Observation 6ff322d2-0b8e-4641-885d-63f033c2b1e1 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Adaptive mixtures of local experts
Reference 17
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Observation 8d115b63-0b99-4016-91a5-b56091d284de · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Identifying and mitigating vulnerabilities in llm-integrated applications
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 15d9fede-8697-47c9-b17f-cd54e020620f · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Reference 19
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Observation 7073d266-c72e-4a0b-999c-6545f0ca91c1 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Less is More: Selective Layer Finetuning with SubTuning
Reference 20
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Observation 476400f6-a7f8-4adc-94f1-13ad6cadf667 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts VeRA: Vector-based Random Matrix Adaptation
Reference 21
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Observation e4011ca0-94cc-44f0-af08-36b777fe1ee2 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Optimal brain damage
Reference 22
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Observation 7424c8fc-b454-4235-843c-f4c8b92703db · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Reference 23
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Unavailable: canonical work link unavailable.
Observation 267a91a9-8fc1-4630-b922-1050960b6381 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Conditional adapters: Parameter-efficient transfer learning with fast inference
Reference 24
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8ac650bd-c276-4e7d-bf25-c907bf2df1a4 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts The Power of Scale for Parameter-Efficient Prompt Tuning
Reference 25
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Unavailable: canonical work link unavailable.
Observation e75d4cba-4d09-4444-882b-d743e9294843 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Prefix-Tuning: Optimizing Continuous Prompts for Generation
Reference 26
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Observation f50f1ee1-0d78-4e8a-98ff-fce668dbe521 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Chatdoctor: A medical chat model fine-tuned on a large language model meta-ai (llama) using medical domain knowledge
Reference 27
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Unavailable: canonical work link unavailable.
Observation 463410fe-f299-4cda-b946-f65651bcc183 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Reference 28
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Observation 7720f447-ffda-46b3-8793-79ddcecee064 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts DoRA: Weight-Decomposed Low-Rank Adaptation
Reference 29
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Observation 63c044d9-1594-43df-a25e-72eaea3b12f8 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Reference 30
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Observation bc2d7b63-5914-4398-b325-88cd06979c10 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Gpt understands, too
Reference 31
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Observation eebf33fb-65d8-42ba-a3b5-b570debd78e9 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts ALoRA: Allocating Low-Rank Adaptation for Fine-tuning Large Language Models
Reference 32
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Observation 9cb5dd07-0a0e-4f7c-b738-0b78eb777066 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts The flan collection: Designing data and methods for effective instruction tuning
Reference 33
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6bce41b6-6fd3-42ea-b72f-9ccd78d319ae · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Llm-pruner: On the structural pruning of large language models
Reference 34
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d99fac71-411c-43cb-ab37-0d7cb3741954 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models
Reference 35
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Observation 7b01ed15-55f5-4760-930e-2c6724856a38 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023
Reference 36
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9b2ca90e-7073-4e19-bd7d-a2da2c2c71a6 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Multi-head adapter routing for cross-task generalization
Reference 37
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4582706e-1f12-4388-9402-9a06cb53819c · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
Reference 38
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Observation 4f3e6791-b887-4ff9-9fb4-2a6882427481 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying
Reference 39
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Observation 74c9f7c5-94c6-444c-bb2b-412accc9cf35 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts On the effect of dropping layers of pre-trained transformer models
Reference 40
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e8c1a75d-c3e5-43c2-8d75-b59da1c84211 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Reference 41
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Observation 538c6522-9b89-4391-8dac-dcca1108c594 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Reference 42
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Observation 6ad5e942-e6d5-46a9-a548-b12eff57d5fa · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Gemma 2: Improving Open Language Models at a Practical Size
Reference 43
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Observation 482b0006-63b8-4908-af19-71a8acc16119 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
Reference 44
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Observation 61b5f1ca-7afa-479a-87cf-bedd8617bc80 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 45
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Observation d672f9e3-34e0-439c-90d1-0522e1fd63e4 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation
Reference 46
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Unavailable: canonical work link unavailable.
Observation 7de5f910-32d8-4ab3-8de0-cd873ccf9534 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Eigendamage: Structured pruning in the kronecker-factored eigenbasis
Reference 47
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dab70a53-010a-4440-aa7a-6607e60ae327 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
Reference 48
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Observation f43b12e6-3060-43a9-ad56-6a47d15013d5 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M
Reference 49
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b202b104-fc60-40bd-ac11-596a10c6a66a · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model
Reference 50
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6f6c7e3b-f613-4e7b-aa57-f37df9495d79 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning
Reference 51
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Observation f82c49eb-4f3b-4c9e-89a4-ce18d4b775f1 · outbound
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Reference 52
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Observation cf0213bb-963b-4605-99a1-ce6dd3a2fdce · inbound
One Algorithm, Two Goals: Dual Scoring for Parameter and Data Selection in LLM Fine-Tuning FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts
Reference 52
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5d6a5c94-e727-46c0-9243-badeb91d54df · inbound
LAARA: Layer-Aware Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts
Reference 9
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Unavailable: canonical work link unavailable.