ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation | Paper Citation Record

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Unresolved cited work

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Fluctuation-based adaptive structured pruning for large language models

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Dynamic context pruning for efficient and interpretable autoregressive transformers

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This paper cites A general language assistant as a laboratory for alignment, 2021.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation A general language assistant as a laboratory for alignment, 2021

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Mitigat- ing open-vocabulary caption hallucinations, 2024

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This paper cites GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow, March 2021.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow, March 2021

Reference 6

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Token Merging: Your ViT But Faster

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Emerging properties in self-supervised vision transformers

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Vision transformer slimming: Multi-dimension searching in continuous optimization space

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Unresolved cited work

Reference 10

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This paper cites The lottery ticket hypothesis for pre-trained bert networks.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation The lottery ticket hypothesis for pre-trained bert networks

Reference 11

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This paper cites The principle of diversity: Training stronger vision transformers calls for reducing all levels of redundancy.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation The principle of diversity: Training stronger vision transformers calls for reducing all levels of redundancy

Reference 12

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation A toy model of universality: Reverse engineering how networks learn group operations

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Training Verifiers to Solve Math Word Problems

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This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Analyzing Redundancy in Pretrained Transformer Models

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Imagenet: A large- scale hierarchical image database

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Qlora: Efficient finetuning of quantized llms

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This paper cites Eventful transformers: leveraging temporal redundancy in vision transformers.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Eventful transformers: leveraging temporal redundancy in vision transformers

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation A mathematical framework for transformer circuits

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Depgraph: Towards any structural pruning

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity, 2022

Reference 22

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Transformer Feed-Forward Layers Are Key-Value Memories

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Successor Heads: Recurring, Interpretable Attention Heads In The Wild

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation MiniLLM: Knowledge distillation of large language models

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This paper cites Learning efficient vision transformers via fine-grained manifold distillation.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Learning efficient vision transformers via fine-grained manifold distillation

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This paper cites Masked autoencoders are scalable vision learners, 2021.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Masked autoencoders are scalable vision learners, 2021

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation What Matters in Transformers? Not All Attention is Needed

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Distilling the Knowledge in a Neural Network

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Mixture of Nested Experts: Adaptive Processing of Visual Tokens

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Self-distillation into self-attention heads for improving transformer-based end-to-end neural speaker diarization

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Expedited training of visual conditioned language generation via redundancy reduction

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Mixtral of Experts

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Self-supervised 3d anatomy segmentation using self-distilled masked image transformer (smit)

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation TinyBERT: Distilling BERT for Natural Language Understanding

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Self-Distillation for Further Pre-training of Transformers

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Clustered imagenet labels for training production-friendly image classifier

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Knowledge distillation via the target-aware transformer

Reference 40

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Visual instruction tuning

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Oscillation-free quantization for low-bit vision transformers

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Post-training quantization for vision transformer

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Anytime Dense Prediction with Confidence Adaptivity

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation A transformer-based model with self-distillation for multimodal emotion recognition in conversations

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Llm-pruner: On the structural pruning of large language models

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Copy Suppression: Comprehensively Understanding an Attention Head

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Locating and editing factual associations in gpt

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Circuit Component Reuse Across Tasks in Transformer Language Models

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Zoom in: An introduction to circuits

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation In-context Learning and Induction Heads

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Ia-red 2: Interpretability-aware redundancy reduction for vision transformers

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Self-evolving vision transformer for chest x-ray diagnosis through knowledge distillation

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This paper cites A practical review of mech- anistic interpretability for transformer-based language models.arXiv preprint arXiv:2407.02646, 2024.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation A practical review of mech- anistic interpretability for transformer-based language models.arXiv preprint arXiv:2407.02646, 2024

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Dynamicvit: Efficient vision transformers with dynamic token sparsification

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 57

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Observation bdf3dd24-01e7-4af5-9c2b-c8b570da2546 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 58

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Observation 39d689fd-4cd5-4e07-8e20-31bc538d89af · outbound

This paper cites Confident adaptive language modeling.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Confident adaptive language modeling

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.513563Z

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Observation 391d1b87-f156-45bc-b39e-55f78eb52bd6 · outbound

This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 60

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Observation 9e457abb-0556-4269-abc2-bfc9f1873c4e · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 61

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Observation 54e6f198-ea37-4b4c-954b-1d271ad9dd34 · outbound

This paper cites A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation Analysis.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation Analysis

Reference 62

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Observation 697491b3-5265-46f7-88e0-6c8627f8810b · outbound

This paper cites Tasked: transformer-based adversarial learning for human activity recognition using wearable sensors via self-knowledge distillation.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Tasked: transformer-based adversarial learning for human activity recognition using wearable sensors via self-knowledge distillation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.505781Z

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Observation 73e114a5-6a81-4076-92a5-f43ba06e4e2d · outbound

This paper cites Self-distilled vision transformer for domain generalization.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Self-distilled vision transformer for domain generalization

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.496992Z

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Observation d3b10aa2-14bb-43f3-b59c-0b57d06a790a · outbound

This paper cites Patient Knowledge Distillation for BERT Model Compression.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Patient Knowledge Distillation for BERT Model Compression

Reference 65

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Observation 8312c520-0e96-41d9-b045-14fd40262c2b · outbound

This paper cites MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

Reference 66

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Observation b47718a4-6be5-4669-90a5-67c84787c257 · outbound

This paper cites Patch slimming for efficient vision transformers.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Patch slimming for efficient vision transformers

Reference 67

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Observation fc3cce1a-9e23-42a2-8fba-d94c5de0578b · outbound

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:38:52.483135Z

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Observation 8378a85f-e41e-4276-9c62-43ec2ac1af75 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Training data-efficient image transformers & distillation through attention

Reference 69

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Observation e3fa46d1-7012-4a75-910a-88ec06df7c40 · outbound

This paper cites Attention is all you need.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Attention is all you need

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:51.969832Z

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Observation 03c70042-9d43-43c0-8c76-c5f78c24529f · outbound

This paper cites Rkld: Reverse kl-divergence- based knowledge distillation for unlearning personal information in large language models, 2024.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Rkld: Reverse kl-divergence- based knowledge distillation for unlearning personal information in large language models, 2024

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.464845Z

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Observation 8adb33bb-3086-440e-b335-7cab20402372 · outbound

This paper cites Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Reference 72

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Observation b62e5c21-9f43-4b81-ab10-ab17702fb178 · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.456906Z

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Observation e24b8f23-3957-4d42-9397-6e0ec64b77d3 · outbound

This paper cites Last: Label-free self-distillation contrastive learning with transformer architecture for remote sensing image scene classification.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Last: Label-free self-distillation contrastive learning with transformer architecture for remote sensing image scene classification

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.448430Z

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Observation 1749f87a-2a79-4e35-ba69-ae658f8d1b8d · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Tinyvit: Fast pretraining distillation for small vision transformers

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.438892Z

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Observation 23cc25b4-72e7-4e58-bf94-be7ee936f505 · outbound

This paper cites Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:51.987271Z

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Observation 233e4718-6d55-4085-a644-6d508d92c1f0 · outbound

This paper cites Structured Pruning Learns Compact and Accurate Models.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Structured Pruning Learns Compact and Accurate Models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:51.990020Z

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Observation 33c2b9fc-d032-40a7-95a7-0384e79a0ba4 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 78

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Observation 33c4be17-a40d-4aa6-935b-01e311898b3d · outbound

This paper cites ThinK: Thinner Key Cache by Query-Driven Pruning.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation ThinK: Thinner Key Cache by Query-Driven Pruning

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:51.995190Z

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Observation 0273513d-35ee-4930-a305-18c2edda9540 · outbound

This paper cites X-pruner: explainable pruning for vision transformers.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation X-pruner: explainable pruning for vision transformers

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.424277Z

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Observation 93c0355e-f848-45db-9b2f-12e6afd37318 · outbound

This paper cites Unified Visual Transformer Compression.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Unified Visual Transformer Compression

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:52.000864Z

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Observation 11a5dcf9-149d-4f7b-b713-3b8c2f8a1686 · outbound

This paper cites MoEfication: Transformer Feed-forward Layers are Mixtures of Experts.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation MoEfication: Transformer Feed-forward Layers are Mixtures of Experts

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:52.004555Z

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Observation caea50ba-6c6e-424d-bb5c-0cc1ee2e5027 · outbound

This paper cites Knowledge distillation based on transformed teacher matching.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Knowledge distillation based on transformed teacher matching

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.414808Z

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Observation 80958d0c-b3c7-4749-8de3-4432ec47e4ca · outbound

This paper cites The clock and the pizza: Two stories in mechanistic explanation of neural networks.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation The clock and the pizza: Two stories in mechanistic explanation of neural networks

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:52.010319Z

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Observation 19db123c-225d-4678-83db-042e11c80ad4 · outbound

This paper cites LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:52.013139Z

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Observation e89b4d73-6cb9-4692-bfff-0be0ab6974aa · outbound

This paper cites MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-12T14:38:52.016407Z

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Observation 2a226cfb-df33-4745-a251-066a3616abc2 · outbound

This paper cites Possible solutions could include:.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Possible solutions could include:

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:38:52.402343Z

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Observation da8cde43-a337-4086-a708-a2e5e522a007 · outbound

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ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:38:52.394336Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 35c4f703-c447-4c33-ad9e-f9b61206eaa1 · outbound

This paper cites an unresolved cited work.

ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:38:52.385463Z

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