TinyBERT: Distilling BERT for Natural Language Understanding | Paper Citation Record

Observation a234e4eb-ab96-46dd-a4c9-9c43c87b8efc · inbound

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer cites this paper.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer TinyBERT: Distilling BERT for Natural Language Understanding

Reference 30

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Observation 2b8ff791-0b26-40cf-bf79-ab2754a1c3ff · inbound

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators cites this paper.

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators TinyBERT: Distilling BERT for Natural Language Understanding

Reference 3

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Language Models are Few-Shot Learners cites this paper.

Language Models are Few-Shot Learners TinyBERT: Distilling BERT for Natural Language Understanding

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:05:38.246816Z

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Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed cites this paper.

Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed TinyBERT: Distilling BERT for Natural Language Understanding

Reference 15

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DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing cites this paper.

DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing TinyBERT: Distilling BERT for Natural Language Understanding

Reference 9

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Fake News Detection After LLM Laundering: Measurement and Explanation cites this paper.

Fake News Detection After LLM Laundering: Measurement and Explanation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 39

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BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts cites this paper.

BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts TinyBERT: Distilling BERT for Natural Language Understanding

Reference 12

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Observation b2f779b1-5788-41e3-a593-46cebc98585b · inbound

On Teacher Hacking in Language Model Distillation cites this paper.

On Teacher Hacking in Language Model Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 2015

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Observation d5d66f28-4c3d-4039-9f6d-cc525750cd45 · inbound

Performance Analysis of Traditional VQA Models Under Limited Computational Resources cites this paper.

Performance Analysis of Traditional VQA Models Under Limited Computational Resources TinyBERT: Distilling BERT for Natural Language Understanding

Reference 21

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Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile cites this paper.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile TinyBERT: Distilling BERT for Natural Language Understanding

Reference 21

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Optimizing Knowledge Distillation in Transformers: Enabling Multi-Head Attention without Alignment Barriers cites this paper.

Optimizing Knowledge Distillation in Transformers: Enabling Multi-Head Attention without Alignment Barriers TinyBERT: Distilling BERT for Natural Language Understanding

Reference 2017

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Observation e7aa24e4-5d35-4d94-90f2-cb1c8ed7de4c · inbound

LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention cites this paper.

LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention TinyBERT: Distilling BERT for Natural Language Understanding

Reference 5

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Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices TinyBERT: Distilling BERT for Natural Language Understanding

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:05:16.228134Z

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A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA TinyBERT: Distilling BERT for Natural Language Understanding

Reference 195

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Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation cites this paper.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 17

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Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data cites this paper.

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data TinyBERT: Distilling BERT for Natural Language Understanding

Reference 19

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SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks cites this paper.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks TinyBERT: Distilling BERT for Natural Language Understanding

Reference 20

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Observation feab6543-dc02-436a-9418-2ff401b5f011 · inbound

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes cites this paper.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes TinyBERT: Distilling BERT for Natural Language Understanding

Reference 4

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Multimodal Medical Image Binding via Shared Text Embeddings cites this paper.

Multimodal Medical Image Binding via Shared Text Embeddings TinyBERT: Distilling BERT for Natural Language Understanding

Reference 21

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Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration TinyBERT: Distilling BERT for Natural Language Understanding

Reference 111

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MobileRAG: A Fast, Memory-Efficient, and Energy-Efficient Method for On-Device RAG cites this paper.

MobileRAG: A Fast, Memory-Efficient, and Energy-Efficient Method for On-Device RAG TinyBERT: Distilling BERT for Natural Language Understanding

Reference 23

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Collaborative Distillation Strategies for Parameter-Efficient Language Model Deployment cites this paper.

Collaborative Distillation Strategies for Parameter-Efficient Language Model Deployment TinyBERT: Distilling BERT for Natural Language Understanding

Reference 23

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Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study cites this paper.

Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study TinyBERT: Distilling BERT for Natural Language Understanding

Reference 28

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Observation 210e109c-ec36-4528-9e09-d2ffdadc1c6c · inbound

Enhanced Arabic Text Retrieval with Attentive Relevance Scoring cites this paper.

Enhanced Arabic Text Retrieval with Attentive Relevance Scoring TinyBERT: Distilling BERT for Natural Language Understanding

Reference 18

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Resource-Efficient Automatic Software Vulnerability Assessment via Knowledge Distillation and Particle Swarm Optimization cites this paper.

Resource-Efficient Automatic Software Vulnerability Assessment via Knowledge Distillation and Particle Swarm Optimization TinyBERT: Distilling BERT for Natural Language Understanding

Reference 83

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Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code cites this paper.

Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code TinyBERT: Distilling BERT for Natural Language Understanding

Reference 66

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GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay cites this paper.

GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay TinyBERT: Distilling BERT for Natural Language Understanding

Reference 18

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Observation d8128c1a-2a38-4318-bbd4-2abaaddc6114 · inbound

Expandable Residual Approximation for Knowledge Distillation cites this paper.

Expandable Residual Approximation for Knowledge Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 60

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Observation d237722c-20c3-403a-ac7a-1da6da367d4c · inbound

AMMKD: Adaptive Multimodal Multi-teacher Distillation for Lightweight Vision-Language Models cites this paper.

AMMKD: Adaptive Multimodal Multi-teacher Distillation for Lightweight Vision-Language Models TinyBERT: Distilling BERT for Natural Language Understanding

Reference 19

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NoteBar: An AI-Assisted Note-Taking System for Personal Knowledge Management cites this paper.

NoteBar: An AI-Assisted Note-Taking System for Personal Knowledge Management TinyBERT: Distilling BERT for Natural Language Understanding

Reference 22

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A Transformer-Based Cross-Platform Analysis of Public Discourse on the 15-Minute City Paradigm cites this paper.

A Transformer-Based Cross-Platform Analysis of Public Discourse on the 15-Minute City Paradigm TinyBERT: Distilling BERT for Natural Language Understanding

Reference 27

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SindBERT, the Sailor: Charting the Seas of Turkish NLP cites this paper.

SindBERT, the Sailor: Charting the Seas of Turkish NLP TinyBERT: Distilling BERT for Natural Language Understanding

Reference 15

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A Metamorphic Testing Perspective on Knowledge Distillation for Language Models of Code: Does the Student Deeply Mimic the Teacher? cites this paper.

A Metamorphic Testing Perspective on Knowledge Distillation for Language Models of Code: Does the Student Deeply Mimic the Teacher? TinyBERT: Distilling BERT for Natural Language Understanding

Reference 79

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DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce cites this paper.

DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce TinyBERT: Distilling BERT for Natural Language Understanding

Reference 42

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FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption cites this paper.

FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption TinyBERT: Distilling BERT for Natural Language Understanding

Reference 38

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A Comparative Study of Semantic Log Representations for Software Log-based Anomaly Detection cites this paper.

A Comparative Study of Semantic Log Representations for Software Log-based Anomaly Detection TinyBERT: Distilling BERT for Natural Language Understanding

Reference 14

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Observation 96155bb0-3b50-42ec-8494-a2a28fc3ce7e · inbound

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations cites this paper.

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations TinyBERT: Distilling BERT for Natural Language Understanding

Reference 22

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Observation 25f667af-963c-44d0-94c7-a96028d9ad73 · inbound

ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting cites this paper.

ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting TinyBERT: Distilling BERT for Natural Language Understanding

Reference 30

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Observation 66b9c556-8e2a-470e-9d30-7d28d44f40b7 · inbound

TabEmb: Joint Semantic-Structure Embedding for Table Annotation cites this paper.

TabEmb: Joint Semantic-Structure Embedding for Table Annotation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 42

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Observation 982c30a7-9243-462e-94c6-e5a1760b57e7 · inbound

SRA: Span Representation Alignment for Large Language Model Distillation cites this paper.

SRA: Span Representation Alignment for Large Language Model Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 3

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Observation 65cc1a51-536f-4b18-8c49-1fafad3490d1 · inbound

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation cites this paper.

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 3

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Observation 37118c6b-3d65-4292-bb06-05684e865599 · inbound

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation cites this paper.

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 1

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Observation bd571544-d7bf-4504-8218-fcae17f48a5a · inbound

Combining pre-trained models via localized model averaging cites this paper.

Combining pre-trained models via localized model averaging TinyBERT: Distilling BERT for Natural Language Understanding

Reference 150

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Observation 5383e0ad-9bee-4442-a9b1-b14883139966 · inbound

BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation cites this paper.

BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:15:11.707359Z

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Observation 0972ee65-ebb9-416a-9456-b21e26496ef5 · inbound

Fast Tensorization of Neural Networks via Slice-wise Feature Distillation cites this paper.

Fast Tensorization of Neural Networks via Slice-wise Feature Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-20T06:53:22.956232Z

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Observation 4582d3fa-d37a-48e4-8a69-d02152f30f1f · inbound

When Mean CE Fails: Median CE Can Better Track Language Model Quality cites this paper.

When Mean CE Fails: Median CE Can Better Track Language Model Quality TinyBERT: Distilling BERT for Natural Language Understanding

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:24:39.948088Z

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Observation 9a691f3c-2803-4f4c-9062-949e31d62082 · inbound

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation cites this paper.

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:53:15.420960Z

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Observation 101f88cd-8ca6-46fd-8d10-41e327910293 · inbound

Do Transformers Need Three Projections? Systematic Study of QKV Variants cites this paper.

Do Transformers Need Three Projections? Systematic Study of QKV Variants TinyBERT: Distilling BERT for Natural Language Understanding

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:36:17.296567Z

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Observation 8b7baf1f-7b74-4503-b001-f22cd9be71ac · inbound

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models cites this paper.

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models TinyBERT: Distilling BERT for Natural Language Understanding

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:16:48.231919Z

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Observation 92c8bb65-0867-4c60-a7f2-1002beef1905 · inbound

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models cites this paper.

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models TinyBERT: Distilling BERT for Natural Language Understanding

Reference 127

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:27:29.554567Z

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Observation b8452aba-1e81-4f52-a05e-fcd27ad94a34 · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection TinyBERT: Distilling BERT for Natural Language Understanding

Reference 65

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T07:11:45.313693Z

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Observation b9da8958-fc6c-43ac-9bc2-c410d7e443c2 · inbound

TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation cites this paper.

TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:40.474904Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2e91149-e5b7-4028-a0bc-ac0aa346ec15 · inbound

Unified Multi-Task Relevance Modeling for E-Commerce: Comparing Task Routing Architectures Across LLMs and Cross-Encoders cites this paper.

Unified Multi-Task Relevance Modeling for E-Commerce: Comparing Task Routing Architectures Across LLMs and Cross-Encoders TinyBERT: Distilling BERT for Natural Language Understanding

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:49:51.880172Z

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Observation 93f2dabb-d093-45ba-a4b3-d0f97a909f9c · inbound

Data Provenance for Image Auto-Regressive Generation cites this paper.

Data Provenance for Image Auto-Regressive Generation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 106

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T10:34:36.631239Z

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Observation 404ba290-802b-4ef5-9456-d52bc53c03e5 · inbound

Vitality-Aware Compression for Efficient Image-to-Shape Diffusion Transformers cites this paper.

Vitality-Aware Compression for Efficient Image-to-Shape Diffusion Transformers TinyBERT: Distilling BERT for Natural Language Understanding

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:07:03.975713Z

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