Advantageous Parameter Expansion Training Makes Better Large Language Models | Paper Citation Record

Observation 1f61e9e3-18a0-4949-819c-8c3922f02abd · outbound

This paper cites GPT-4 Technical Report.

Advantageous Parameter Expansion Training Makes Better Large Language Models GPT-4 Technical Report

Reference 1

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Advantageous Parameter Expansion Training Makes Better Large Language Models Mistral 7B

Reference 2

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Advantageous Parameter Expansion Training Makes Better Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 3

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

Advantageous Parameter Expansion Training Makes Better Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 4

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This paper cites Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J.

Advantageous Parameter Expansion Training Makes Better Large Language Models Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J

Reference 5

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This paper cites Internlm2 technical report, 2024.

Advantageous Parameter Expansion Training Makes Better Large Language Models Internlm2 technical report, 2024

Reference 6

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This paper cites Qwen2 technical report, 2024.

Advantageous Parameter Expansion Training Makes Better Large Language Models Qwen2 technical report, 2024

Reference 7

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This paper cites Smith, Iz Beltagy, and Hannaneh Hajishirzi.

Advantageous Parameter Expansion Training Makes Better Large Language Models Smith, Iz Beltagy, and Hannaneh Hajishirzi

Reference 8

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This paper cites PiSSA: Principal singular values and singular vectors adaptation of large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models PiSSA: Principal singular values and singular vectors adaptation of large language models

Reference 9

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Observation 016d757b-1a1d-4f55-a4b2-6e9a78f6e201 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Advantageous Parameter Expansion Training Makes Better Large Language Models The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 10

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This paper cites A win-win deal: Towards sparse and robust pre-trained language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models A win-win deal: Towards sparse and robust pre-trained language models

Reference 11

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This paper cites The lottery LLM hypothesis, rethinking what abilities should LLM compression preserve? In The Fourth Blogpost Track at ICLR 2025, 2025.

Advantageous Parameter Expansion Training Makes Better Large Language Models The lottery LLM hypothesis, rethinking what abilities should LLM compression preserve? In The Fourth Blogpost Track at ICLR 2025, 2025

Reference 12

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Observation f03907e4-aaae-4ae3-8829-63c601ff2a46 · outbound

This paper cites LLM-pruner: On the structural pruning of large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models LLM-pruner: On the structural pruning of large language models

Reference 13

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This paper cites Fluctuation-based adaptive structured pruning for large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models Fluctuation-based adaptive structured pruning for large language models

Reference 14

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This paper cites Discovering sparsity allocation for layer-wise pruning of large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models Discovering sparsity allocation for layer-wise pruning of large language models

Reference 15

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This paper cites Structured optimal brain pruning for large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models Structured optimal brain pruning for large language models

Reference 16

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This paper cites A simple and effective pruning approach for large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models A simple and effective pruning approach for large language models

Reference 17

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This paper cites Dauphin, Angela Fan, Michael Auli, and David Grangier.

Advantageous Parameter Expansion Training Makes Better Large Language Models Dauphin, Angela Fan, Michael Auli, and David Grangier

Reference 18

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This paper cites Training Verifiers to Solve Math Word Problems.

Advantageous Parameter Expansion Training Makes Better Large Language Models Training Verifiers to Solve Math Word Problems

Reference 19

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

Advantageous Parameter Expansion Training Makes Better Large Language Models Sheared LLaMA: Accelerating language model pre-training via structured pruning

Reference 20

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Advantageous Parameter Expansion Training Makes Better Large Language Models Unresolved cited work

Reference 21

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Advantageous Parameter Expansion Training Makes Better Large Language Models Unresolved cited work

Reference 22

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This paper cites Massive activations in large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models Massive activations in large language models

Reference 23

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This paper cites Learning to grow pretrained models for efficient transformer training.

Advantageous Parameter Expansion Training Makes Better Large Language Models Learning to grow pretrained models for efficient transformer training

Reference 24

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Observation b1e2a199-25e4-4da0-955c-8541b01e3a29 · outbound

This paper cites LEMON: Lossless model expansion.

Advantageous Parameter Expansion Training Makes Better Large Language Models LEMON: Lossless model expansion

Reference 25

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This paper cites Compute better spent: Replacing dense layers with structured matrices.

Advantageous Parameter Expansion Training Makes Better Large Language Models Compute better spent: Replacing dense layers with structured matrices

Reference 26

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Observation bceaa59f-f172-424d-b3d3-1d9f58602c0b · outbound

This paper cites LEMON: Reviving stronger and smaller LMs from larger LMs with linear parameter fusion.

Advantageous Parameter Expansion Training Makes Better Large Language Models LEMON: Reviving stronger and smaller LMs from larger LMs with linear parameter fusion

Reference 27

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This paper cites Effective rank and the staircase phenomenon: New insights into neural network training dynamics, 2025.

Advantageous Parameter Expansion Training Makes Better Large Language Models Effective rank and the staircase phenomenon: New insights into neural network training dynamics, 2025

Reference 28

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This paper cites Goodfellow, and Jonathon Shlens.

Advantageous Parameter Expansion Training Makes Better Large Language Models Goodfellow, and Jonathon Shlens

Reference 29

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This paper cites bert2BERT: Towards reusable pretrained language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models bert2BERT: Towards reusable pretrained language models

Reference 30

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This paper cites Peters, and Iz Beltagy.

Advantageous Parameter Expansion Training Makes Better Large Language Models Peters, and Iz Beltagy

Reference 31

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This paper cites Hft: Half fine-tuning for large language models, 2024.

Advantageous Parameter Expansion Training Makes Better Large Language Models Hft: Half fine-tuning for large language models, 2024

Reference 32

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This paper cites Enhancing large language model performance with gradient-based parameter selection.

Advantageous Parameter Expansion Training Makes Better Large Language Models Enhancing large language model performance with gradient-based parameter selection

Reference 33

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This paper cites Llama 2: Open foundation and fine-tuned chat models, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Llama 2: Open foundation and fine-tuned chat models, 2023

Reference 34

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This paper cites Measuring massive multitask language understanding.

Advantageous Parameter Expansion Training Makes Better Large Language Models Measuring massive multitask language understanding

Reference 35

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This paper cites Challenging BIG-bench tasks and whether chain-of-thought can solve them.

Advantageous Parameter Expansion Training Makes Better Large Language Models Challenging BIG-bench tasks and whether chain-of-thought can solve them

Reference 36

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This paper cites Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki.

Advantageous Parameter Expansion Training Makes Better Large Language Models Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki

Reference 37

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This paper cites TruthfulQA: Measuring how models mimic human falsehoods.

Advantageous Parameter Expansion Training Makes Better Large Language Models TruthfulQA: Measuring how models mimic human falsehoods

Reference 38

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This paper cites Evaluating Large Language Models Trained on Code.

Advantageous Parameter Expansion Training Makes Better Large Language Models Evaluating Large Language Models Trained on Code

Reference 39

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This paper cites Parameter-efficient transfer learning for NLP.

Advantageous Parameter Expansion Training Makes Better Large Language Models Parameter-efficient transfer learning for NLP

Reference 40

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This paper cites DoRA: Weight-decomposed low-rank adaptation.

Advantageous Parameter Expansion Training Makes Better Large Language Models DoRA: Weight-decomposed low-rank adaptation

Reference 41

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Advantageous Parameter Expansion Training Makes Better Large Language Models ReloRA: High-rank training through low-rank updates

Reference 42

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Observation c4a3b13a-206f-4367-8b78-c5c51632f429 · outbound

This paper cites S2ft: Efficient, scalable and generalizable llm fine-tuning by structured sparsity.

Advantageous Parameter Expansion Training Makes Better Large Language Models S2ft: Efficient, scalable and generalizable llm fine-tuning by structured sparsity

Reference 43

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This paper cites Tinyllama: An open-source small language model, 2024.

Advantageous Parameter Expansion Training Makes Better Large Language Models Tinyllama: An open-source small language model, 2024

Reference 44

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This paper cites Redpajama: an open dataset for training large language models.

Advantageous Parameter Expansion Training Makes Better Large Language Models Redpajama: an open dataset for training large language models

Reference 45

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This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Advantageous Parameter Expansion Training Makes Better Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 46

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This paper cites The LAMBADA dataset: Word prediction requiring a broad discourse context.

Advantageous Parameter Expansion Training Makes Better Large Language Models The LAMBADA dataset: Word prediction requiring a broad discourse context

Reference 47

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This paper cites LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning.

Advantageous Parameter Expansion Training Makes Better Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 48

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This paper cites PIQA: reasoning about physical commonsense in natural language.

Advantageous Parameter Expansion Training Makes Better Large Language Models PIQA: reasoning about physical commonsense in natural language

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:06.045296Z

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This paper cites Liu, and Matt Gardner.

Advantageous Parameter Expansion Training Makes Better Large Language Models Liu, and Matt Gardner

Reference 50

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This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Advantageous Parameter Expansion Training Makes Better Large Language Models Winogrande: An adversarial winograd schema challenge at scale

Reference 51

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This paper cites Hellaswag: Can a machine really finish your sentence? In Anna Korhonen, David R.

Advantageous Parameter Expansion Training Makes Better Large Language Models Hellaswag: Can a machine really finish your sentence? In Anna Korhonen, David R

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.937552Z

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Observation cb37b043-42b9-40fc-b629-463701300ea5 · outbound

This paper cites Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M.

Advantageous Parameter Expansion Training Makes Better Large Language Models Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.828632Z

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Observation f5c64eae-1e07-464e-bb4f-a00198043064 · outbound

This paper cites Learning to grow pretrained models for efficient transformer training.

Advantageous Parameter Expansion Training Makes Better Large Language Models Learning to grow pretrained models for efficient transformer training

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.725310Z

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Observation edaeab5a-93e2-42ac-9b31-451cc37f11f8 · outbound

This paper cites Scaling smart: Accelerating large language model pre-training with small model initialization, 2024.

Advantageous Parameter Expansion Training Makes Better Large Language Models Scaling smart: Accelerating large language model pre-training with small model initialization, 2024

Reference 55

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Observation 598d78ce-bc8f-4b66-815c-ed79b1be4e7a · outbound

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

Advantageous Parameter Expansion Training Makes Better Large Language Models LoRA: Low-rank adaptation of large language models

Reference 56

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Observation 0ea1ddef-4d6d-4ab5-b4cf-47c4f6b43f7b · outbound

This paper cites Parameter-efficient transfer learning with diff pruning.

Advantageous Parameter Expansion Training Makes Better Large Language Models Parameter-efficient transfer learning with diff pruning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.442392Z

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Observation 75f589f9-b90d-4873-a779-047b624455da · outbound

This paper cites Training neural networks with fixed sparse masks.

Advantageous Parameter Expansion Training Makes Better Large Language Models Training neural networks with fixed sparse masks

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.310344Z

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Observation 093b258c-5123-43bb-9923-a5fa2272b0d5 · outbound

This paper cites LoRAMoE: Alleviating world knowledge forgetting in large language models via MoE-style plugin.

Advantageous Parameter Expansion Training Makes Better Large Language Models LoRAMoE: Alleviating world knowledge forgetting in large language models via MoE-style plugin

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.178736Z

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Observation 1e9fb02a-8604-4f43-96d7-2373da49bb66 · outbound

This paper cites Open llm leaderboard v2.

Advantageous Parameter Expansion Training Makes Better Large Language Models Open llm leaderboard v2

Reference 60

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Observation 60bab649-cf82-4e8e-b539-38e4d438d58f · outbound

This paper cites Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V.

Advantageous Parameter Expansion Training Makes Better Large Language Models Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.074193Z

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Observation b744294a-9da6-412b-82d9-a1c3ef8ee8b8 · outbound

This paper cites Openassistant conversations – democratizing large language model alignment, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Openassistant conversations – democratizing large language model alignment, 2023

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.145796Z

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Observation d59716fd-d1ed-4e31-bf53-d803417fc55e · outbound

This paper cites Instruction tuning with gpt-4, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Instruction tuning with gpt-4, 2023

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.223776Z

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Observation 24e2876f-de3c-43f0-9dae-195d802dab98 · outbound

This paper cites Code alpaca: An instruction-following llama model for code generation.

Advantageous Parameter Expansion Training Makes Better Large Language Models Code alpaca: An instruction-following llama model for code generation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.322828Z

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This paper cites Lima: Less is more for alignment, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Lima: Less is more for alignment, 2023

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.414462Z

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This paper cites Wizardlm: Empowering large language models to follow complex instructions, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Wizardlm: Empowering large language models to follow complex instructions, 2023

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:05.021454Z

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Observation 606314cf-158d-4628-8818-55b540c64291 · outbound

This paper cites Orca: Progressive learning from complex explanation traces of gpt-4, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Orca: Progressive learning from complex explanation traces of gpt-4, 2023

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.573739Z

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Observation d5b397c3-3d60-4168-8ae1-d4814a079de6 · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:03.689722Z

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Observation 7eeb2cf9-8b95-4754-a4be-b9ba879c25bd · outbound

This paper cites composer.https://github.com/mosaicml/composer/, 2021.

Advantageous Parameter Expansion Training Makes Better Large Language Models composer.https://github.com/mosaicml/composer/, 2021

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:04.853208Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 68637e74-e185-4a2e-befc-228cd5ccc64e · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling, 2023.

Advantageous Parameter Expansion Training Makes Better Large Language Models Pythia: A suite for analyzing large language models across training and scaling, 2023

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:04.711088Z

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Observation 474f2d64-e64a-4264-9ded-cb63ac899a0a · outbound

This paper cites The language model evaluation harness, 07 2024.

Advantageous Parameter Expansion Training Makes Better Large Language Models The language model evaluation harness, 07 2024

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:04.518059Z

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Observation e1820a5a-e5ab-4162-81b9-bf11f68c613d · outbound

This paper cites [68], we fine-tune them for 3 epochs.

Advantageous Parameter Expansion Training Makes Better Large Language Models [68], we fine-tune them for 3 epochs

Reference 8192

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:36:04.368810Z

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