Delta Activations: A Representation for Finetuned Large Language Models | Paper Citation Record

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This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Delta Activations: A Representation for Finetuned Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

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This paper cites Perception Encoder: The best visual embeddings are not at the output of the network.

Delta Activations: A Representation for Finetuned Large Language Models Perception Encoder: The best visual embeddings are not at the output of the network

Reference 2

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Delta Activations: A Representation for Finetuned Large Language Models Enhancing human-like responses in large language models

Reference 3

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Delta Activations: A Representation for Finetuned Large Language Models Generative pretraining from pixels

Reference 4

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Delta Activations: A Representation for Finetuned Large Language Models Adaptersoup: Weight averaging to improve generalization of pretrained language models

Reference 5

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This paper cites Scaling instruction-finetuned language models.

Delta Activations: A Representation for Finetuned Large Language Models Scaling instruction-finetuned language models

Reference 6

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Delta Activations: A Representation for Finetuned Large Language Models Training Verifiers to Solve Math Word Problems

Reference 7

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Delta Activations: A Representation for Finetuned Large Language Models Codechef

Reference 8

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This paper cites Ultrafeedback: Boosting language models with scaled ai feedback.

Delta Activations: A Representation for Finetuned Large Language Models Ultrafeedback: Boosting language models with scaled ai feedback

Reference 9

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Delta Activations: A Representation for Finetuned Large Language Models Unresolved cited work

Reference 10

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This paper cites Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence.

Delta Activations: A Representation for Finetuned Large Language Models Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence

Reference 11

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This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot.

Delta Activations: A Representation for Finetuned Large Language Models Sparsegpt: Massive language models can be accurately pruned in one-shot

Reference 12

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This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

Delta Activations: A Representation for Finetuned Large Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 13

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This paper cites Disease database.

Delta Activations: A Representation for Finetuned Large Language Models Disease database

Reference 14

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This paper cites Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N.

Delta Activations: A Representation for Finetuned Large Language Models Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N

Reference 15

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Delta Activations: A Representation for Finetuned Large Language Models Learning both weights and connections for efficient neural network

Reference 16

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This paper cites Localize-and-stitch: Efficient model merging via sparse task arithmetic.

Delta Activations: A Representation for Finetuned Large Language Models Localize-and-stitch: Efficient model merging via sparse task arithmetic

Reference 17

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This paper cites Distilling the Knowledge in a Neural Network.

Delta Activations: A Representation for Finetuned Large Language Models Distilling the Knowledge in a Neural Network

Reference 18

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This paper cites Unsupervised model tree heritage recovery.

Delta Activations: A Representation for Finetuned Large Language Models Unsupervised model tree heritage recovery

Reference 19

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

Delta Activations: A Representation for Finetuned Large Language Models LoRA: Low-rank adaptation of large language models

Reference 20

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This paper cites Lorahub: Efficient cross-task generalization via dynamic lora composition.

Delta Activations: A Representation for Finetuned Large Language Models Lorahub: Efficient cross-task generalization via dynamic lora composition

Reference 21

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This paper cites OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models.

Delta Activations: A Representation for Finetuned Large Language Models OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Reference 22

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Delta Activations: A Representation for Finetuned Large Language Models Editing models with task arithmetic

Reference 23

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Delta Activations: A Representation for Finetuned Large Language Models Smith, Iz Beltagy, and Hannaneh Hajishirzi

Reference 24

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This paper cites What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams.

Delta Activations: A Representation for Finetuned Large Language Models What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Reference 25

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Delta Activations: A Representation for Finetuned Large Language Models Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection

Reference 26

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Delta Activations: A Representation for Finetuned Large Language Models Pubmedqa: A dataset for biomedical research question answering

Reference 27

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This paper cites Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights.

Delta Activations: A Representation for Finetuned Large Language Models Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights

Reference 28

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Delta Activations: A Representation for Finetuned Large Language Models Matrix factorization techniques for recom- mender systems

Reference 29

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Delta Activations: A Representation for Finetuned Large Language Models Imagenet classification with deep convolutional neural networks

Reference 30

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Delta Activations: A Representation for Finetuned Large Language Models Optimal brain damage

Reference 31

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Delta Activations: A Representation for Finetuned Large Language Models Emergent world representations: Exploring a sequence model trained on a synthetic task

Reference 32

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Delta Activations: A Representation for Finetuned Large Language Models Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights

Reference 33

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Delta Activations: A Representation for Finetuned Large Language Models Awq: Activation- aware weight quantization for llm compression and acceleration

Reference 34

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Delta Activations: A Representation for Finetuned Large Language Models DeepSeek-V3 Technical Report

Reference 35

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Delta Activations: A Representation for Finetuned Large Language Models In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

Reference 36

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Delta Activations: A Representation for Finetuned Large Language Models Meaning representations from trajectories in autoregressive models

Reference 37

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Delta Activations: A Representation for Finetuned Large Language Models Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models

Reference 38

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Delta Activations: A Representation for Finetuned Large Language Models Pace: Parsimonious concept engineering for large language models

Reference 39

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Delta Activations: A Representation for Finetuned Large Language Models Stylus: Automatic adapter selection for diffusion models

Reference 40

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Delta Activations: A Representation for Finetuned Large Language Models Wizardcoder: Empowering code large language models with evol-instruct

Reference 41

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Delta Activations: A Representation for Finetuned Large Language Models Simpo: Simple preference optimization with a reference-free reward

Reference 42

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Delta Activations: A Representation for Finetuned Large Language Models Efficient estimation of word representations in vector space

Reference 43

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Delta Activations: A Representation for Finetuned Large Language Models Disease-symptoms dataset

Reference 44

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Delta Activations: A Representation for Finetuned Large Language Models SGPT: GPT Sentence Embeddings for Semantic Search

Reference 45

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Delta Activations: A Representation for Finetuned Large Language Models Routellm: Learning to route llms from preference data

Reference 46

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Delta Activations: A Representation for Finetuned Large Language Models Task arithmetic in the tangent space: Improved editing of pre-trained models

Reference 47

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Delta Activations: A Representation for Finetuned Large Language Models Towards Modular LLMs by Building and Reusing a Library of LoRAs

Reference 48

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Delta Activations: A Representation for Finetuned Large Language Models Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.498028Z

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This paper cites Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive.

Delta Activations: A Representation for Finetuned Large Language Models Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive

Reference 50

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This paper cites Codeelo: Benchmarking competition-level code generation of llms with human-comparable elo ratings, 2025.

Delta Activations: A Representation for Finetuned Large Language Models Codeelo: Benchmarking competition-level code generation of llms with human-comparable elo ratings, 2025

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.483941Z

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This paper cites Direct preference optimization: Your language model is secretly a reward model.

Delta Activations: A Representation for Finetuned Large Language Models Direct preference optimization: Your language model is secretly a reward model

Reference 52

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Delta Activations: A Representation for Finetuned Large Language Models Learning dynamics of llm finetuning

Reference 53

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Delta Activations: A Representation for Finetuned Large Language Models Rousseeuw

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.447940Z

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Observation c9ac31a0-0410-4bcd-8bd4-0b886abd2d9a · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

Delta Activations: A Representation for Finetuned Large Language Models Large Language Model Routing with Benchmark Datasets

Reference 55

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This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Delta Activations: A Representation for Finetuned Large Language Models A Simple and Effective Pruning Approach for Large Language Models

Reference 56

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Observation 1a5b33fa-4054-4e01-8a5e-9fea87d3e9f5 · outbound

This paper cites Zico Kolter, and Zhuang Liu.

Delta Activations: A Representation for Finetuned Large Language Models Zico Kolter, and Zhuang Liu

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.434281Z

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Observation 2084aa51-711c-4a44-acc1-18411fef60f4 · outbound

This paper cites Zico Kolter, and Zhuang Liu.

Delta Activations: A Representation for Finetuned Large Language Models Zico Kolter, and Zhuang Liu

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.420106Z

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Observation 0aa7a8ed-d2e5-4870-9029-3e490557caaf · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Delta Activations: A Representation for Finetuned Large Language Models Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.584823Z

Source-reported events for the cited work

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Observation 980c1259-a3e7-42dd-a11d-9415d4f9b4f8 · outbound

This paper cites Learnware of Language Models: Specialized Small Language Models Can Do Big.

Delta Activations: A Representation for Finetuned Large Language Models Learnware of Language Models: Specialized Small Language Models Can Do Big

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-15T16:32:08.918648Z

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Observation 1c0b89ae-be85-41f1-b4eb-70b0b0fa06e7 · outbound

This paper cites Alpaca: A strong, replicable instruction-following model.

Delta Activations: A Representation for Finetuned Large Language Models Alpaca: A strong, replicable instruction-following model

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.404220Z

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Observation e1209b46-6d8c-48a4-b368-8ccbe7bfd953 · outbound

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

Delta Activations: A Representation for Finetuned Large Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.597650Z

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Observation 4ea137ba-0a3e-4836-aa5f-d5d17b28602e · outbound

This paper cites Contrastive Representation Distillation.

Delta Activations: A Representation for Finetuned Large Language Models Contrastive Representation Distillation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.601956Z

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Observation af525828-1da8-4852-bd34-63d2f2e8accb · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Delta Activations: A Representation for Finetuned Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.606212Z

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Observation dbd2046c-fcc5-47ef-b859-5c1b65515298 · outbound

This paper cites Neural Network Diffusion.

Delta Activations: A Representation for Finetuned Large Language Models Neural Network Diffusion

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.610494Z

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Observation 997cd79a-81f1-4fd5-acd4-833db2647dec · outbound

This paper cites MiniLMv2: Multi-head self-attention relation distillation for compressing pretrained transformers.

Delta Activations: A Representation for Finetuned Large Language Models MiniLMv2: Multi-head self-attention relation distillation for compressing pretrained transformers

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.390108Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c0701a2d-42d7-40fb-abdb-45794ab56043 · outbound

This paper cites Sheared LLaMA: Accelerating language model pre-training via structured pruning.

Delta Activations: A Representation for Finetuned Large Language Models Sheared LLaMA: Accelerating language model pre-training via structured pruning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.376285Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0a29b9f2-0308-485b-bbe3-8c0b99fbc3a2 · outbound

This paper cites Initializing models with larger ones.

Delta Activations: A Representation for Finetuned Large Language Models Initializing models with larger ones

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.362416Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c4b3b5ee-60db-4356-847a-62242e709901 · outbound

This paper cites Qwen2.5 Technical Report.

Delta Activations: A Representation for Finetuned Large Language Models Qwen2.5 Technical Report

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.627457Z

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Observation 34718942-5f39-4802-882d-e39c908bc14d · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

Delta Activations: A Representation for Finetuned Large Language Models Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.631926Z

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Observation e0f43d3f-f8d2-42ae-ae1f-deaa3e0bce1e · outbound

This paper cites Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.

Delta Activations: A Representation for Finetuned Large Language Models Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.636003Z

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Observation f5cc9eae-0f07-44b2-9666-b252b5a93390 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Delta Activations: A Representation for Finetuned Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.640819Z

Source-reported events for the cited work

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Observation c4c40920-7fc8-4c64-b645-9b5cc6bf667a · outbound

This paper cites Neural phylogeny: Fine-tuning relationship detection among neural networks.

Delta Activations: A Representation for Finetuned Large Language Models Neural phylogeny: Fine-tuning relationship detection among neural networks

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.348637Z

Source-reported events for the cited work

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Observation c99d9f80-d600-4cc1-a359-c8286a16875a · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In ACL, 2019.

Delta Activations: A Representation for Finetuned Large Language Models Hellaswag: Can a machine really finish your sentence? In ACL, 2019

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.649880Z

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Observation b19375b8-802d-42cb-b111-a713d1f36f17 · outbound

This paper cites Generative modeling of weights: General- ization or memorization? arXiv preprint arXiv:2506.07998, 2025.

Delta Activations: A Representation for Finetuned Large Language Models Generative modeling of weights: General- ization or memorization? arXiv preprint arXiv:2506.07998, 2025

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.653768Z

Source-reported events for the cited work

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Observation 6e7bf94e-0a31-4c96-be21-cd49f0a0b0c6 · outbound

This paper cites Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs.

Delta Activations: A Representation for Finetuned Large Language Models Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.658364Z

Source-reported events for the cited work

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Observation 665fce63-c13c-40fc-8b1e-475cb3461df3 · outbound

This paper cites LoraRetriever: Input-aware LoRA retrieval and composition for mixed tasks in the wild.

Delta Activations: A Representation for Finetuned Large Language Models LoraRetriever: Input-aware LoRA retrieval and composition for mixed tasks in the wild

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.325568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0955bc0e-d9e7-4d4a-96fb-5e4033538886 · outbound

This paper cites A comprehensive survey on transfer learning.

Delta Activations: A Representation for Finetuned Large Language Models A comprehensive survey on transfer learning

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.666511Z

Source-reported events for the cited work

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Observation 7dcf9caf-dcfb-4b9a-b2d9-25c4dc8772dc · outbound

This paper cites meaning vector.

Delta Activations: A Representation for Finetuned Large Language Models meaning vector

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:32:09.302295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 46bd37af-6871-411d-8ce7-82d95270512e · outbound

This paper cites Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic.

Delta Activations: A Representation for Finetuned Large Language Models Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T16:32:08.402542Z

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