Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T15:36:04.620053Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2502.01378.
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 2026-08-09T15:36:04.620053Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:53:42.543595Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T04:53:45.038200Z
61 of 61 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7a99774b-1535-48d4-aff4-ec432bf0b684 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models On the Opportunities and Risks of Foundation Models
Reference 1
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Observation b374afaf-2a6c-4e7f-b23c-a16a5ca5012c · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Instruction tuning for large language models: A survey
Reference 2
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Observation 2d138c26-9b1d-4a67-a0c0-a548582c3d2e · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Reference 3
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Observation 5d6740cb-8757-4397-a187-de45c8499f91 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models LoRA: Low-Rank Adaptation of Large Language Models
Reference 4
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Observation f8cbc10f-3f9a-4eba-a107-4f7af0d997a5 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Fast monte carlo algorithms for matrices i: Approximating matrix multiplication
Reference 5
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Observation 0d736b1c-f510-4699-95a1-8a7ed4df2900 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Accelerating large language models through partially linear feed-forward network
Reference 6
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Observation 42e27d34-5e5c-4151-97a6-a70ab70c01d5 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models First Activations Matter: Training-Free Methods for Dynamic Activation in Large Language Models
Reference 7
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Observation 56d9ee7b-bcd1-435f-99cd-ea56ddb9ad75 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications
Reference 8
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Observation 053bfaed-9abf-489c-bb52-339420b18400 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models LSAQ: Layer-Specific Adaptive Quantization for Large Language Model Deployment
Reference 9
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Observation 26d22641-5be1-453b-bcca-af9996668f5f · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
Reference 10
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Observation c11586e7-efe1-4040-8e5d-32a54250d0bc · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients
Reference 11
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Observation e86f556c-2ba9-45b0-9480-61098180e33a · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Training-Free Activation Sparsity in Large Language Models
Reference 12
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Observation 02a9849c-69e5-4728-a0db-a743ccbcbe25 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models
Reference 13
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Observation 3dfa33b9-e66c-46cc-9151-9ec1a845eb0c · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Unresolved cited work
Reference 15
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Observation b5e68911-353a-40b8-91ea-89cef1e505db · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Dolan and Chris Brockett
Reference 16
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Observation 004d61e4-e93d-4ec9-a92d-4a16360dc3a7 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Unresolved cited work
Reference 17
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Observation 49532871-cfae-462d-b631-bc9d06910a5b · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models BoolQ: Exploring the surprising difficulty of natural yes/no questions
Reference 18
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Observation ef933af0-e74b-4b49-9c25-d00bd8288461 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Piqa: Reasoning about phys- ical commonsense in natural language
Reference 19
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Unavailable: canonical work link unavailable.
Observation a7f429e3-185e-47ce-bae0-732a356b76ac · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models SocialIQA: Commonsense Reasoning about Social Interactions
Reference 20
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Unavailable: canonical work link unavailable.
Observation a487be32-e9df-4b2f-bdf2-21825767e103 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models HellaSwag: Can a Machine Really Finish Your Sentence?
Reference 21
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Observation 88eae423-85ee-4608-8743-d23f73943131 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Winogrande: An adversarial winograd schema challenge at scale
Reference 22
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Observation ce8b0b48-48b6-4c80-a99d-838a19683567 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 23
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Observation ecc1dff6-be7a-4d7b-aa89-880a23302ca2 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
Reference 24
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Observation 7e52f85e-e1a6-4a72-a7fd-810aeb40f650 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Solving General Arithmetic Word Problems
Reference 25
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Observation dcd6a529-f118-489c-897e-dc45e5114cc1 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Training Verifiers to Solve Math Word Problems
Reference 26
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Observation 7cd19fc0-b7a5-452d-b5ff-9015eacd5ca8 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Learning to solve arithmetic word problems with verb categorization
Reference 27
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Observation 5120e42f-836b-4cf5-bc13-e0379b6e6fda · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Program induction by rationale generation: Learning to solve and explain algebraic word problems
Reference 28
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Observation 8a3a4dcc-5bf0-4a2f-9943-24926d6da7ba · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Parsing algebraic word problems into equations
Reference 29
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Observation d4aab167-4347-4a18-b0d1-6567589f69c2 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Unresolved cited work
Reference 30
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Observation 8a8982f4-86c7-4029-b7eb-153b53ec0bc4 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models MAWPS: A math word problem repository
Reference 31
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Observation 796d26dd-92fb-445d-b2e1-e52056049789 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Llama 2: Open foundation and fine-tuned chat models, 2023
Reference 32
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Observation 71479d94-dfef-42d1-9708-ab453b7b9174 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Llama 3 model card
Reference 33
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Observation 11b5314d-38b4-46a4-b6ab-eb045cb51925 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Attention is all you need
Reference 34
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Observation 906cc04e-9410-4e80-a887-8eb1e57b0711 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Improving language understanding by generative pre-training
Reference 35
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Observation cde9661f-7e2a-4b15-af4d-7b67c1b20c2b · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Language models are unsupervised multitask learners
Reference 36
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Observation c86edbe3-7a32-4c3a-840c-d3f60995661d · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Language models are few-shot learners
Reference 37
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Observation c1dd38b1-9c3a-4c41-874c-9696f866578e · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models OPT: Open Pre-trained Transformer Language Models
Reference 38
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Observation 19309529-df6a-4457-bcd3-bea4486e426e · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models LLaMA: Open and Efficient Foundation Language Models
Reference 39
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Observation 4f1c1232-f414-4e3e-bed3-74c31b37b8f5 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 40
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Observation b791e550-9fce-42cd-8ef9-33c354a64def · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models The Llama 3 Herd of Models
Reference 41
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Observation cb9227cc-62e5-438a-bfdc-6b29ac800c0b · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Bloom: A 176b-parameter open-access multilingual language model
Reference 42
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Observation 2a648d4e-cc30-483e-8642-ede31c079dff · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference 43
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Observation f3ae2700-0bca-4105-8dfa-cc8ac20764d1 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only
Reference 44
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Observation 9ab0943b-1e86-4ac2-894c-369b9ddf5a22 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Parameter-efficient transfer learning for nlp
Reference 45
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Observation 3a80791f-8fa5-4756-8f50-68105d016cfb · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models AdapterHub: A Framework for Adapting Transformers
Reference 46
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Observation f6f0e3fd-d2c0-4beb-bd59-181a6cf11535 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Relora: High- rank training through low-rank updates
Reference 47
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Observation abc781bc-f05c-4772-a1f8-6438a374a6ed · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models S$^{2}$FT: Efficient, scalable and generalizable LLM fine-tuning by structured sparsity
Reference 48
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Observation 828a1067-31be-409d-bf22-9cdd11ee32d0 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining
Reference 49
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Observation 5b35d931-cb0a-4ea5-ae22-bd8a186a8584 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
Reference 50
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Observation 8163b80d-d668-4393-ac9d-ae4bab343c4a · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Reference 51
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Observation dfac57be-e5e6-4ba9-8383-5e67cd2b3517 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Subspace Optimization for Large Language Models with Convergence Guarantees
Reference 52
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Observation 90c3e789-de35-4d12-ba7f-00a8d4aed1e0 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Reference 53
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Observation e0758e33-bda0-4aca-9cb0-f0d89f52189c · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Back razor: Memory-efficient transfer learning by self-sparsified backpropagation
Reference 54
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Observation a1e9e345-4ecc-47db-8603-01d3f18c8a71 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Sheared back- propagation for fine-tuning foundation models
Reference 55
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Observation 634db3ce-5d63-410d-98fd-a21824293f93 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Mixed Precision Training
Reference 56
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Observation 4f345764-70c8-4294-9e7e-b086a8e8e989 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Qlora: Efficient finetuning of quantized llms
Reference 57
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Observation 5f0b7288-dee8-4114-b32d-914e834b639b · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models APOLLO: SGD-like Memory, AdamW-level Performance
Reference 58
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Observation dde316be-93f3-4f55-bfb5-36f4c2dd0173 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
Reference 59
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Observation 9faff1bb-5271-4124-88c3-f2164ea7bcb8 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Unresolved cited work
Reference 60
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Observation 7b4b0cc1-937e-4c1b-ba6a-274839a4ecba · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Unresolved cited work
Reference 61
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Observation edce4c6c-da2f-4de1-94a8-67175cca20e2 · outbound
CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Unresolved cited work
Reference 2017
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Observation f666ed42-bca9-4958-aeaa-5aa3a8b2ff96 · inbound
From over-reliance to smart integration: using Large-Language Models as translators between specialized modeling and simulation tools CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models
Reference 2025
Source-reported events for the cited work
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