Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:25:29.332228Z
Paper Citation Record · LEDGER
Improving LoRA with Variational Learning
As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 2 inbound Pith citation observations for arXiv:2506.14280.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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 2026-06-26T09:00:50.315383Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T10:19:47.216056Z
Reference resolution
59 of 59 outbound references displayed
- verified exact1
- verified fuzzy44
- unresolved14
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 6b3da705-d471-42eb-92c0-8e05f2151e05 · outbound
This paper cites Stop measuring calibration when humans disagree.
Improving LoRA with Variational Learning Stop measuring calibration when humans disagree
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.231706Z
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 58c484c4-c21f-4f18-a086-c31faa8584dc · outbound
This paper cites BitFit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.
Improving LoRA with Variational Learning BitFit: Simple parameter-efficient fine-tuning for transformer-based masked language-models
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.216470Z
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 14426df0-6280-47e0-a207-c0cedd8e3f42 · outbound
This paper cites LoRA Learns Less and Forgets Less.
Improving LoRA with Variational Learning LoRA Learns Less and Forgets Less
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.109933Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3457a43-e7d7-44e2-b797-7ea3e941780b · outbound
This paper cites Weight uncertainty in neural network.
Improving LoRA with Variational Learning Weight uncertainty in neural network
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.200861Z
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 91c25571-1a12-4de7-a057-0ea560460770 · outbound
This paper cites A Bayesian Interpretation of Adaptive Low-Rank Adaptation.
Improving LoRA with Variational Learning A Bayesian Interpretation of Adaptive Low-Rank Adaptation
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:25:29.503979Z
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 9a0a1ebb-ada5-445b-959f-9bfe5b647ebd · outbound
This paper cites BoolQ: Exploring the surprising difficulty of natural yes/no questions.
Improving LoRA with Variational Learning BoolQ: Exploring the surprising difficulty of natural yes/no questions
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.185897Z
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 36f1f6a0-e93f-4663-b5fb-5025c130fc9d · outbound
This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.
Improving LoRA with Variational Learning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.127431Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 602c26ef-ea1d-40e2-b4c6-9b35060458be · outbound
This paper cites Training Verifiers to Solve Math Word Problems.
Improving LoRA with Variational Learning Training Verifiers to Solve Math Word Problems
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.131646Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 390e371a-a2d1-4407-b688-a15bf328220b · outbound
This paper cites Uncertainty-aware decoding with minimum Bayes risk.
Improving LoRA with Variational Learning Uncertainty-aware decoding with minimum Bayes risk
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.170376Z
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 e1fda1a3-2cb8-48ce-8493-0ad8ca6140b6 · outbound
This paper cites QLoRA: Efficient finetuning of quantized LLMs.
Improving LoRA with Variational Learning QLoRA: Efficient finetuning of quantized LLMs
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.155101Z
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 d7fa154b-c410-46ea-b3fb-90ab5d0a50c4 · outbound
This paper cites Shaving weights with Occam’s razor: Bayesian sparsification for neural networks using the marginal likelihood.
Improving LoRA with Variational Learning Shaving weights with Occam’s razor: Bayesian sparsification for neural networks using the marginal likelihood
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.140988Z
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 f0504c87-0eac-4ce2-beef-7d50ee9cb4c2 · outbound
This paper cites Sparse low-rank adaptation of pre-trained language models.
Improving LoRA with Variational Learning Sparse low-rank adaptation of pre-trained language models
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.124769Z
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 6f0349e3-5e1d-46de-bd61-373f499ca5db · outbound
This paper cites The Llama 3 Herd of Models.
Improving LoRA with Variational Learning The Llama 3 Herd of Models
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.152895Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f0a47b2-1cf1-4a0c-b37a-e8a5d9a1ff17 · outbound
This paper cites Practical variational inference for neural networks.
Improving LoRA with Variational Learning Practical variational inference for neural networks
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.109354Z
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 885d12a3-ae6c-4041-9379-db87b4d7c990 · outbound
This paper cites The safe Bayesian - learning the learning rate via the mixability gap.
Improving LoRA with Variational Learning The safe Bayesian - learning the learning rate via the mixability gap
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.093600Z
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 43707d77-5f29-4886-8c3d-dcfc5f3fdd07 · outbound
This paper cites DeBERTa: Decoding-enhanced BERT with disentangled attention.
Improving LoRA with Variational Learning DeBERTa: Decoding-enhanced BERT with disentangled attention
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.079213Z
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 e918ddc4-cd08-43d7-a507-a19c62c8ce60 · outbound
This paper cites SparseAdapter: An easy approach for improving the parameter-efficiency of adapters.
Improving LoRA with Variational Learning SparseAdapter: An easy approach for improving the parameter-efficiency of adapters
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.063915Z
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 caa998e5-a75f-4f77-811d-acc56ea5957a · outbound
This paper cites Measuring massive multitask language understanding.
Improving LoRA with Variational Learning Measuring massive multitask language understanding
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.172974Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d34cd46a-a379-4276-991a-a181e5b3f24d · outbound
This paper cites Parameter-efficient transfer learning for NLP.
Improving LoRA with Variational Learning Parameter-efficient transfer learning for NLP
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.038491Z
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 8c996251-5cdf-4fab-b0ea-79a19fcce51c · outbound
This paper cites LoRA: Low-rank adaptation of large language models.
Improving LoRA with Variational Learning LoRA: Low-rank adaptation of large language models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.181019Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1068b262-ee3b-491e-93f4-04f4e708745d · outbound
This paper cites Improving predictions of Bayesian neural nets via local linearization.
Improving LoRA with Variational Learning Improving predictions of Bayesian neural nets via local linearization
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:30.009267Z
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 2208dcc4-62c4-4502-ba39-3b73a00d3446 · outbound
This paper cites VeRA: Vector-based random matrix adaptation.
Improving LoRA with Variational Learning VeRA: Vector-based random matrix adaptation
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.993862Z
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 d9695b21-d584-45eb-9991-8cbb51027614 · outbound
This paper cites Optimal brain damage.
Improving LoRA with Variational Learning Optimal brain damage
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.978638Z
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 4b8c8797-c967-4302-985e-39f25c8c08e0 · outbound
This paper cites Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape.
Improving LoRA with Variational Learning Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.196199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b67813c7-a7e0-4c94-936a-08ccaf8ce762 · outbound
This paper cites Prefix-tuning: Optimizing continuous prompts for generation.
Improving LoRA with Variational Learning Prefix-tuning: Optimizing continuous prompts for generation
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.200628Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd451574-c404-4fdc-9f9b-cc2112ec902c · outbound
This paper cites LoftQ: LoRA-fine-tuning-aware quantization for large language models.
Improving LoRA with Variational Learning LoftQ: LoRA-fine-tuning-aware quantization for large language models
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.954356Z
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 62d79341-215b-44a3-9896-55a3a32c1014 · outbound
This paper cites ReLoRA: High-rank training through low-rank updates.
Improving LoRA with Variational Learning ReLoRA: High-rank training through low-rank updates
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.939354Z
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 946918ef-8022-40cb-93eb-828c753a2186 · outbound
This paper cites PAC-tuning: Fine- tuning pre-trained language models with PAC-driven perturbed gradient descent.
Improving LoRA with Variational Learning PAC-tuning: Fine- tuning pre-trained language models with PAC-driven perturbed gradient descent
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.924767Z
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 e4d83b86-b7e7-4e4d-b9f1-130c9de1d2dc · outbound
This paper cites Decoupled weight decay regularization.
Improving LoRA with Variational Learning Decoupled weight decay regularization
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.216325Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90815848-f2e5-419e-8427-c7cceb005f55 · outbound
This paper cites A practical Bayesian framework for backpropagation networks.Neural Computation, 4(3):448–472, 1992.
Improving LoRA with Variational Learning A practical Bayesian framework for backpropagation networks.Neural Computation, 4(3):448–472, 1992
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.898944Z
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 0cd344cc-59e1-456b-99c4-8e52de1b5d60 · outbound
This paper cites PEFT: State-of-the-art parameter-efficient fine-tuning methods.
Improving LoRA with Variational Learning PEFT: State-of-the-art parameter-efficient fine-tuning methods
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.884479Z
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 fab6502d-a449-4776-8b4b-2042c1ad502f · outbound
This paper cites Optimizing neural networks with Kronecker-factored approximate curvature.
Improving LoRA with Variational Learning Optimizing neural networks with Kronecker-factored approximate curvature
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.869600Z
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 0ce8cd33-eeda-4662-9a9d-db59977cb1d7 · outbound
This paper cites Can a suit of armor conduct electricity? A new dataset for open book question answering.
Improving LoRA with Variational Learning Can a suit of armor conduct electricity? A new dataset for open book question answering
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.855641Z
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 4193f3eb-e563-41aa-b127-bdc87451a1f1 · outbound
This paper cites Gaussian stochastic weight averaging for Bayesian low-rank adaptation of large language models.
Improving LoRA with Variational Learning Gaussian stochastic weight averaging for Bayesian low-rank adaptation of large language models
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.841637Z
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 bc2bf0f9-65bf-432c-8605-fc5d7448da73 · outbound
This paper cites MAD-X: An adapter-based framework for multi-task cross-lingual transfer.
Improving LoRA with Variational Learning MAD-X: An adapter-based framework for multi-task cross-lingual transfer
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.827335Z
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 0c0ae5c8-d62e-4596-bce1-aad7ce26898f · outbound
This paper cites Adapters: A unified library for parameter- efficient and modular transfer learning.
Improving LoRA with Variational Learning Adapters: A unified library for parameter- efficient and modular transfer learning
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.812960Z
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 f347a1da-ea79-4a0b-826c-54f82b7eef2a · outbound
This paper cites CodeBLEU: a Method for Automatic Evaluation of Code Synthesis.
Improving LoRA with Variational Learning CodeBLEU: a Method for Automatic Evaluation of Code Synthesis
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.246224Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8781e06-31f0-48b7-89bf-cf10bb12dc08 · outbound
This paper cites A scalable Laplace approximation for neural networks.
Improving LoRA with Variational Learning A scalable Laplace approximation for neural networks
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.797996Z
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 13f0d611-9561-4c56-9246-b84275000764 · outbound
This paper cites AdapterDrop: On the efficiency of adapters in transformers.
Improving LoRA with Variational Learning AdapterDrop: On the efficiency of adapters in transformers
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.783281Z
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 99e1b380-fec2-42cb-8e0f-4c2e5a37b35f · outbound
This paper cites WinoGrande: An adversarial Winograd schema challenge at scale.Communications of the ACM, 2021.
Improving LoRA with Variational Learning WinoGrande: An adversarial Winograd schema challenge at scale.Communications of the ACM, 2021
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.769495Z
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 b14bc861-ab3a-427a-b44d-c3bdec6d78b7 · outbound
This paper cites Variational learning is effective for large deep networks.
Improving LoRA with Variational Learning Variational learning is effective for large deep networks
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.755625Z
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 a38cc89f-f3b4-4334-9636-dc1019253326 · outbound
This paper cites Qwen2.5 Technical Report.
Improving LoRA with Variational Learning Qwen2.5 Technical Report
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.265033Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 861e8892-36d8-444b-ad66-504c425ef040 · outbound
This paper cites DyLoRA: Parameter-efficient tuning of pre-trained models using dynamic search-free low-rank adaptation.
Improving LoRA with Variational Learning DyLoRA: Parameter-efficient tuning of pre-trained models using dynamic search-free low-rank adaptation
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.740162Z
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 5c66d683-d364-4bf8-880e-1477a73fe9f1 · outbound
This paper cites Low-rank variational Bayes correction to the Laplace method.J.
Improving LoRA with Variational Learning Low-rank variational Bayes correction to the Laplace method.J
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.726131Z
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 7a0495a6-6699-4916-984c-3f3889760069 · outbound
This paper cites Attention is all you need.
Improving LoRA with Variational Learning Attention is all you need
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.712637Z
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 828ee94a-e4de-489a-aab8-7152a114aeeb · outbound
This paper cites an unresolved cited work.
Improving LoRA with Variational Learning Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T00:25:29.698776Z
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 50e598d1-ec09-4b6e-a718-9db0435e8114 · outbound
This paper cites LoRA ensembles for large language model fine-tuning, 2023.
Improving LoRA with Variational Learning LoRA ensembles for large language model fine-tuning, 2023
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.684144Z
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 7e81976f-031d-43c6-9568-83e372f7bdb0 · outbound
This paper cites BLoB: Bayesian low-rank adaptation by backpropagation for large language models.
Improving LoRA with Variational Learning BLoB: Bayesian low-rank adaptation by backpropagation for large language models
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.669699Z
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 7ec8add5-bb00-4423-9e66-bcdb672f265d · outbound
This paper cites Flipout: Efficient pseudo-independent weight perturbations on mini-batches.
Improving LoRA with Variational Learning Flipout: Efficient pseudo-independent weight perturbations on mini-batches
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.655776Z
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 90df9c00-cf89-44f1-8543-020f7cd836e9 · outbound
This paper cites QA-LoRA: Quantization-aware low-rank adaptation of large language models.
Improving LoRA with Variational Learning QA-LoRA: Quantization-aware low-rank adaptation of large language models
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.640819Z
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 899a76d2-cb5a-4ea0-8d00-9ae27413d051 · outbound
This paper cites Bayesian low-rank adaptation for large language models.
Improving LoRA with Variational Learning Bayesian low-rank adaptation for large language models
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.626524Z
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 8224c14f-81da-40f0-9ea0-407bd04b10ad · outbound
This paper cites Learning to mine aligned code and natural language pairs from Stack Overflow.
Improving LoRA with Variational Learning Learning to mine aligned code and natural language pairs from Stack Overflow
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.611550Z
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 82294ea9-1903-4cc5-907d-eaa28701bd5b · outbound
This paper cites Optimal information processing and Bayes’s theorem.The American Statistician, 42(4): 278–280, 1988.
Improving LoRA with Variational Learning Optimal information processing and Bayes’s theorem.The American Statistician, 42(4): 278–280, 1988
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.596625Z
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 86159505-56da-466d-b389-dda41e029302 · outbound
This paper cites LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning.
Improving LoRA with Variational Learning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.312251Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9160d823-5b5f-4b4b-9d3b-b0722f69a28a · outbound
This paper cites Adaptive budget allocation for parameter-efficient fine-tuning.
Improving LoRA with Variational Learning Adaptive budget allocation for parameter-efficient fine-tuning
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.581734Z
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 00f2be46-7cec-4668-87e4-d8b29a15dee6 · outbound
This paper cites From ε-entropy to KL-entropy: Analysis of minimum information complexity density estimation.The Annals of Statistics, 2006.
Improving LoRA with Variational Learning From ε-entropy to KL-entropy: Analysis of minimum information complexity density estimation.The Annals of Statistics, 2006
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.567063Z
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 c7005290-dc20-4d64-b071-9661a2aa3008 · outbound
This paper cites GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs.
Improving LoRA with Variational Learning GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:25:29.324004Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e55ae8a3-9b2f-4268-91bd-f30c36331644 · outbound
This paper cites True"/"False.
Improving LoRA with Variational Learning True"/"False
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.552336Z
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 89e5c1ad-c9be-4996-b647-7f0aba80de15 · outbound
This paper cites For full-parameter and LoRA finetuning, we pick1×10 −4 and5×10 −4, respectively.
Improving LoRA with Variational Learning For full-parameter and LoRA finetuning, we pick1×10 −4 and5×10 −4, respectively
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:25:29.538004Z
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.
Pith citing papers
Observation d211204b-78a3-479f-a4ac-b64760ce5723 · inbound
Variational Visual Question Answering for Uncertainty-Aware Selective Prediction cites this paper.
Variational Visual Question Answering for Uncertainty-Aware Selective Prediction Improving LoRA with Variational Learning
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T15:31:44.818828Z
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 e8eff5b2-29a8-4b09-ae04-15eff84003cc · inbound
SOAP-Bubbles: Structured Weight Uncertainty for Neural Networks cites this paper.
SOAP-Bubbles: Structured Weight Uncertainty for Neural Networks Improving LoRA with Variational Learning
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T10:19:47.217412Z
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.