LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models | Paper Citation Record

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

WizardLM: Empowering large pre-trained language models to follow complex instructions LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 19

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A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 39

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Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 101

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PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model cites this paper.

PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 30

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Interactive Cycle Model: The Linkage Combination among Automatic Speech Recognition, Large Language Models and Smart Glasses cites this paper.

Interactive Cycle Model: The Linkage Combination among Automatic Speech Recognition, Large Language Models and Smart Glasses LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 2424

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LoRA-Mini : Adaptation Matrices Decomposition and Selective Training cites this paper.

LoRA-Mini : Adaptation Matrices Decomposition and Selective Training LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 16

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Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges cites this paper.

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 155

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KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language Models cites this paper.

KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 23

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S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity cites this paper.

S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 28

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BoRA: Bi-dimensional Weight-Decomposed Low-Rank Adaptation cites this paper.

BoRA: Bi-dimensional Weight-Decomposed Low-Rank Adaptation LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 10

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Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN cites this paper.

Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 13

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Towards a Unified Paradigm: Integrating Recommendation Systems as a New Language in Large Models cites this paper.

Towards a Unified Paradigm: Integrating Recommendation Systems as a New Language in Large Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 18

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DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models cites this paper.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 14

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Efficient Multi-Task Inferencing with a Shared Backbone and Lightweight Task-Specific Adapters for Automatic Scoring cites this paper.

Efficient Multi-Task Inferencing with a Shared Backbone and Lightweight Task-Specific Adapters for Automatic Scoring LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 4

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From Newswire to Nexus: Using text-based actor embeddings and transformer networks to forecast conflict dynamics cites this paper.

From Newswire to Nexus: Using text-based actor embeddings and transformer networks to forecast conflict dynamics LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 2106

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A Survey on Large Language Models with some Insights on their Capabilities and Limitations cites this paper.

A Survey on Large Language Models with some Insights on their Capabilities and Limitations LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 285

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TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning cites this paper.

TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 22

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SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training cites this paper.

SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 6

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Low-Rank Adapters Meet Neural Architecture Search for LLM Compression cites this paper.

Low-Rank Adapters Meet Neural Architecture Search for LLM Compression LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 9

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CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization cites this paper.

CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 12

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Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs cites this paper.

Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

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Sparse Gradient Compression for Fine-Tuning Large Language Models cites this paper.

Sparse Gradient Compression for Fine-Tuning Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

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RandLoRA: Full-rank parameter-efficient fine-tuning of large models cites this paper.

RandLoRA: Full-rank parameter-efficient fine-tuning of large models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

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CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models cites this paper.

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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A Lightweight Method to Disrupt Memorized Sequences in LLM cites this paper.

A Lightweight Method to Disrupt Memorized Sequences in LLM LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 32

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PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 254

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Graph-Based Spectral Decomposition for Parameter Coordination in Language Model Fine-Tuning cites this paper.

Graph-Based Spectral Decomposition for Parameter Coordination in Language Model Fine-Tuning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 23

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Federated Adapter on Foundation Models: An Out-Of-Distribution Approach cites this paper.

Federated Adapter on Foundation Models: An Out-Of-Distribution Approach LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 18

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LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades cites this paper.

LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

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CoIn: Counting the Invisible Reasoning Tokens in Commercial Opaque LLM APIs cites this paper.

CoIn: Counting the Invisible Reasoning Tokens in Commercial Opaque LLM APIs LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 9

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On the Generalization vs Fidelity Paradox in Knowledge Distillation cites this paper.

On the Generalization vs Fidelity Paradox in Knowledge Distillation LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 18

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MAP: Revisiting Weight Decomposition for Low-Rank Adaptation cites this paper.

MAP: Revisiting Weight Decomposition for Low-Rank Adaptation LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 26

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Weight Spectra Induced Efficient Model Adaptation cites this paper.

Weight Spectra Induced Efficient Model Adaptation LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 24

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Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution cites this paper.

Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 2025

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Advantageous Parameter Expansion Training Makes Better Large Language Models cites this paper.

Advantageous Parameter Expansion Training Makes Better Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 68

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Taming LLMs by Scaling Learning Rates with Gradient Grouping cites this paper.

Taming LLMs by Scaling Learning Rates with Gradient Grouping LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 26

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Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models cites this paper.

Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 34

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Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps cites this paper.

Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 40

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Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 130

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Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning cites this paper.

Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

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Open-Vocabulary Object Detection in UAV Imagery: A Review and Future Perspectives cites this paper.

Open-Vocabulary Object Detection in UAV Imagery: A Review and Future Perspectives LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 95

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HuggingGraph: Understanding the Supply Chain of LLM Ecosystem cites this paper.

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 22

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Learning Text Styles: A Study on Transfer, Attribution, and Verification cites this paper.

Learning Text Styles: A Study on Transfer, Attribution, and Verification LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 61

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Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri--Rao Product cites this paper.

Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri--Rao Product LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 25

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RTTC: Reward-Guided Collaborative Test-Time Compute cites this paper.

RTTC: Reward-Guided Collaborative Test-Time Compute LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 35

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HyperAdapt: Simple High-Rank Adaptation cites this paper.

HyperAdapt: Simple High-Rank Adaptation LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 17

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BoHA: Blockwise Hadamard Product Adaptation for Parameter-Efficient Fine-Tuning cites this paper.

BoHA: Blockwise Hadamard Product Adaptation for Parameter-Efficient Fine-Tuning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 8

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LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis cites this paper.

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 8

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Observation 54cf3c14-2a1c-4558-b490-dc29050695f1 · inbound

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis cites this paper.

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 2022

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Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models cites this paper.

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 10

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CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging cites this paper.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 14

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Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions cites this paper.

Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 2

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Observation c4bd3618-c596-4fd0-b7e3-c4f5bef898a2 · inbound

TLoRA: Task-aware Low Rank Adaptation of Large Language Models cites this paper.

TLoRA: Task-aware Low Rank Adaptation of Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:48:48.128101Z

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 e307ce98-8749-4c93-80b1-749e4f5dad88 · inbound

Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning cites this paper.

Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:21:09.746325Z

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 feb5c839-4e61-4ceb-9780-968240db0c9f · inbound

R-CoT: A Reasoning-Layer Watermark via Redundant Chain-of-Thought in Large Language Models cites this paper.

R-CoT: A Reasoning-Layer Watermark via Redundant Chain-of-Thought in Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-12T00:01:16.646974Z

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 01332645-c432-425d-a36e-6e898de63d9e · inbound

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs cites this paper.

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:44:42.655641Z

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 fe5e839b-61a3-46ef-a501-15c2a0fe2df3 · inbound

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs cites this paper.

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:34:57.589775Z

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 c085a2da-b249-4e52-8ce7-66874215e62e · inbound

FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning cites this paper.

FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:23.885550Z

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 2686421f-c5b0-4b85-ba90-c9662eee822c · inbound

Feature Geometry of LoRA Adapters: A Sparse Autoencoder Analysis of Representational Divergence in Fine-Tuned Language Models cites this paper.

Feature Geometry of LoRA Adapters: A Sparse Autoencoder Analysis of Representational Divergence in Fine-Tuned Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:53:28.766324Z

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 b0cbf305-1d70-4ebc-9268-8be421534acf · inbound

Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models cites this paper.

Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:39:37.905715Z

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 2e070690-7432-4f89-9411-eadca9a51fac · inbound

V-FiLLM: Verified Financial LLM Reasoning Benchmark cites this paper.

V-FiLLM: Verified Financial LLM Reasoning Benchmark LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T11:27:14.538468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

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Pith citing papers