Model Connectomes: A Generational Approach to Data-Efficient Language Models | Paper Citation Record

Observation 4d110ecf-2242-4105-9e6b-b208315bbc22 · outbound

This paper cites Love, Christopher J.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Love, Christopher J

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:40.247779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9d9e3e3b-4847-4fb9-bf21-ddf2ef912d38 · outbound

This paper cites Language in brains, minds, and machines.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Language in brains, minds, and machines

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:40.235303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f3c0130b-74fc-43f3-a6d2-25488aa5f18c · outbound

This paper cites Catalyzing next-generation artificial intelligence through neuroai.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Catalyzing next-generation artificial intelligence through neuroai

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:40.221108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 753ef396-f075-482e-ab59-4b48b438a06f · outbound

This paper cites A deep learning framework for neuroscience.

Model Connectomes: A Generational Approach to Data-Efficient Language Models A deep learning framework for neuroscience

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:40.105481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2f68d6b6-ab98-4dba-b41c-bce855bbbe8a · outbound

This paper cites How learning can guide evolution.Complex Systems, 1(3):495–502, 1987.

Model Connectomes: A Generational Approach to Data-Efficient Language Models How learning can guide evolution.Complex Systems, 1(3):495–502, 1987

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:40.051332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bc4cc8da-6aeb-4394-98af-a7acd95ef290 · outbound

This paper cites A critique of pure learning and what artificial neural networks can learn from animal brains.

Model Connectomes: A Generational Approach to Data-Efficient Language Models A critique of pure learning and what artificial neural networks can learn from animal brains

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.563530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da27f7a5-dd02-463a-8263-9d1fc5cb8ac0 · outbound

This paper cites Direct fit to nature: an evolutionary perspective on biological and artificial neural networks.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Direct fit to nature: an evolutionary perspective on biological and artificial neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:40.019141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 88aea36e-2f99-4dac-a493-1c66489ba031 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.921884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d9908253-d2c3-40de-829a-e9363bfe50ca · outbound

This paper cites What artificial neural networks can tell us about human language acquisition.

Model Connectomes: A Generational Approach to Data-Efficient Language Models What artificial neural networks can tell us about human language acquisition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.823314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 08308dcd-dfbd-46f0-9853-da31175175f5 · outbound

This paper cites Call for Papers -- The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Call for Papers -- The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.585620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c72c09ff-d846-4c8d-a138-2ab5634dd399 · outbound

This paper cites Improving language understanding by generative pre-training.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Improving language understanding by generative pre-training

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.591064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d9cf620-6544-48d9-94a9-d4912dce77a1 · outbound

This paper cites Llama v3: Next-generation foundation language model, 2023.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Llama v3: Next-generation foundation language model, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.804369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 55e3afe8-31e4-44d0-9d45-f3ea5bb30ce2 · outbound

This paper cites Deepseek llm: Advancing deep information retrieval with large language models, 2023.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Deepseek llm: Advancing deep information retrieval with large language models, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.791343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d2090d3c-a12d-468d-8fb1-815e8621c80b · outbound

This paper cites Scaling laws for neural language mod- els, 2020.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Scaling laws for neural language mod- els, 2020

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.622434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c5264a8f-23a5-4f38-a242-0b978cead91c · outbound

This paper cites Incorporating context into language encoding models for fmri.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Incorporating context into language encoding models for fmri

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.609632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b132da2-3b35-46b6-a6d8-7c687630ddaf · outbound

This paper cites Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain).

Model Connectomes: A Generational Approach to Data-Efficient Language Models Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.613989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82448664-fc0b-415b-bcdb-15e898c57658 · outbound

This paper cites an unresolved cited work.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-16T05:38:39.550873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation abcc7647-97a8-4e40-b0c9-acce367a1d11 · outbound

This paper cites Brains and algorithms partially converge in natural language processing.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Brains and algorithms partially converge in natural language processing

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.538166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2c8b4712-e539-44f2-a3d5-96b69d627e31 · outbound

This paper cites Shared computational principles for language processing in humans and deep language models.Nature neuroscience, 25(3):369–380, 2022.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Shared computational principles for language processing in humans and deep language models.Nature neuroscience, 25(3):369–380, 2022

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.526094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 28edc966-e31f-491a-a822-086dcf49fb6e · outbound

This paper cites Gptq: Accu- rate post-training quantization for generative pre-trained transformers, 2022.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Gptq: Accu- rate post-training quantization for generative pre-trained transformers, 2022

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.512898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b642b35f-a803-4871-a8d7-aed2b4319e68 · outbound

This paper cites Movement pruning: Adaptive sparsity by fine-tuning.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Movement pruning: Adaptive sparsity by fine-tuning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.361650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a4b9809c-6559-487e-8b0d-bc197a322a83 · outbound

This paper cites Le, Geoffrey Hinton, and Jeff Dean.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Le, Geoffrey Hinton, and Jeff Dean

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.249143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3e952e49-9bba-460d-8688-654f9f702a41 · outbound

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

Model Connectomes: A Generational Approach to Data-Efficient Language Models The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.236828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6bfdd6fb-c911-4407-9c98-66f8344f728a · outbound

This paper cites Unmasking the lottery ticket hypothesis: What’s encoded in a winning ticket’s mask? In Proceedings of the International Conference on Learning Representations (ICLR), 2023.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Unmasking the lottery ticket hypothesis: What’s encoded in a winning ticket’s mask? In Proceedings of the International Conference on Learning Representations (ICLR), 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.224674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 752bce38-be6d-43b6-975a-312552e59892 · outbound

This paper cites Lottery ticket adaptation: Mitigating destructive interference in llms,.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Lottery ticket adaptation: Mitigating destructive interference in llms,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.211602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8671004e-9552-460d-947a-5075dfc47a99 · outbound

This paper cites Lottery tickets in llms: Robustness to adversarial examples via binary masking.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Lottery tickets in llms: Robustness to adversarial examples via binary masking

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.021129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2e2c4ac0-bf54-40b8-8214-6af3c756bd95 · outbound

This paper cites Sparse winning tickets are data-efficient image recognizers.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Sparse winning tickets are data-efficient image recognizers

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:39.007385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 742e369a-c452-478c-bf6e-695260a217b9 · outbound

This paper cites Pruning neural networks without any data by iteratively conserving synaptic flow.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Pruning neural networks without any data by iteratively conserving synaptic flow

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.793208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e68d300f-80e5-4d0f-a432-d30459a21f65 · outbound

This paper cites Deconstructing lottery tickets: Zeros, signs, and the supermask.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Deconstructing lottery tickets: Zeros, signs, and the supermask

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.981519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 837cedff-ab58-4cdc-96ef-101ee91b6335 · outbound

This paper cites Complex com- putation from developmental priors.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Complex com- putation from developmental priors

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.964389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 767c8859-9eac-4353-b896-ae8f3f747d0e · outbound

This paper cites Encoding innate ability through a genomic bottleneck.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Encoding innate ability through a genomic bottleneck

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.854759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a0d292c-1290-40b0-8d0f-2d059dd7fb94 · outbound

This paper cites Enhancing Interpretability using Human Similarity Judgements to Prune Word Embeddings.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Enhancing Interpretability using Human Similarity Judgements to Prune Word Embeddings

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:38:37.882693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 81a7c370-8c94-416e-b6f1-4b2f2e023429 · outbound

This paper cites Pruning sparse features for cognitive modeling.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Pruning sparse features for cognitive modeling

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.936037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8b7f8df6-4d05-4ea5-82be-ef36ae693424 · outbound

This paper cites American parenting of language-learning children: Persisting differences in family-child interactions observed in natural home environments.

Model Connectomes: A Generational Approach to Data-Efficient Language Models American parenting of language-learning children: Persisting differences in family-child interactions observed in natural home environments

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.846134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad1ad28f-c94c-4d7f-b403-02b818144886 · outbound

This paper cites The fineweb datasets: Decanting the web for the finest text data at scale.

Model Connectomes: A Generational Approach to Data-Efficient Language Models The fineweb datasets: Decanting the web for the finest text data at scale

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.807054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0baff369-1489-43e2-a941-bd67b0aeddc8 · outbound

This paper cites modded-nanogpt: Speedrunning the nanogpt baseline, 2024.

Model Connectomes: A Generational Approach to Data-Efficient Language Models modded-nanogpt: Speedrunning the nanogpt baseline, 2024

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.063219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aed2d034-f9c5-4ff1-b6f5-37b5ceae8c62 · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proceedings of the AAAI Conference on Artificial Intelligence, pages 11867–11878.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Hellaswag: Can a machine really finish your sentence? In Proceedings of the AAAI Conference on Artificial Intelligence, pages 11867–11878

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.775155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c07068fe-7f11-4a98-9164-6fb764ed2d39 · outbound

This paper cites Measuring massive multitask language understanding, 2021.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Measuring massive multitask language understanding, 2021

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.719658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3893c908-c4f7-4e8d-b696-046adee30bf2 · outbound

This paper cites On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior.

Model Connectomes: A Generational Approach to Data-Efficient Language Models On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.077764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1643366-2c6a-4774-ab3f-fac6818b2efe · outbound

This paper cites an unresolved cited work.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-16T05:38:38.583094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d433734-0b38-4c10-81cb-f6f6fd608e95 · outbound

This paper cites Word frequency and predictability dissociate in naturalistic reading.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Word frequency and predictability dissociate in naturalistic reading

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.087051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b9d2d8a-c70c-47c7-a85e-51d704e6aa22 · outbound

This paper cites A probabilistic earley parser as a psycholinguistic model.

Model Connectomes: A Generational Approach to Data-Efficient Language Models A probabilistic earley parser as a psycholinguistic model

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.472801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 650d84ce-6ebf-4182-b207-73e219070ff1 · outbound

This paper cites The effect of word predictability on reading time is loga- rithmic.

Model Connectomes: A Generational Approach to Data-Efficient Language Models The effect of word predictability on reading time is loga- rithmic

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.455863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be048b5d-8b92-4f8b-92ca-6ce5087cada6 · outbound

This paper cites The natural stories corpus: a reading-time corpus of english texts containing rare syntactic constructions.

Model Connectomes: A Generational Approach to Data-Efficient Language Models The natural stories corpus: a reading-time corpus of english texts containing rare syntactic constructions

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.440629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7aaf19c9-8c2b-496b-aba6-69af289bd8f9 · outbound

This paper cites Instruction-tuning Aligns LLMs to the Human Brain.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Instruction-tuning Aligns LLMs to the Human Brain

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.106333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf37a86a-c9a9-4d48-a1b6-9d1c67a3cbb6 · outbound

This paper cites Brain-Like Language Processing via a Shallow Untrained Multihead Attention Network.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Brain-Like Language Processing via a Shallow Untrained Multihead Attention Network

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:38:37.794971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 553d5476-c038-4380-bef2-dcb384fba41d · outbound

This paper cites Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:38:37.773705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1c02f142-52d3-4add-8f10-4658bd39ad2b · outbound

This paper cites Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.244659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2387bb5e-23d0-46cc-be17-ba414cad24d3 · outbound

This paper cites Frequency Explains the Inverse Correlation of Large Language Models' Size, Training Data Amount, and Surprisal's Fit to Reading Times.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Frequency Explains the Inverse Correlation of Large Language Models' Size, Training Data Amount, and Surprisal's Fit to Reading Times

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.248750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9493fcf3-225d-406b-9ab9-903ef787e29c · outbound

This paper cites Scaling in cognitive modelling: A multilingual approach to human reading times.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Scaling in cognitive modelling: A multilingual approach to human reading times

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.417594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 41a9b749-1c28-482c-83b7-dbc864e9572f · outbound

This paper cites New method for fmri investigations of language: defining rois functionally in individual subjects.

Model Connectomes: A Generational Approach to Data-Efficient Language Models New method for fmri investigations of language: defining rois functionally in individual subjects

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.341021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7ae4d640-0dc5-4ba1-9b2f-a529a00305a8 · outbound

This paper cites Driving and suppressing the human lan- guage network using large language models.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Driving and suppressing the human lan- guage network using large language models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.240553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 24434a2b-9c2e-4632-84d6-1302fafc7148 · outbound

This paper cites The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units.

Model Connectomes: A Generational Approach to Data-Efficient Language Models The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.265820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 486719cd-ea37-4c03-82ce-bd1aa03f9ef4 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Distilling the Knowledge in a Neural Network

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.270182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03ec4639-98df-49e4-b019-4624cb7722ff · outbound

This paper cites Big self-supervised models are strong semi-supervised learners.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Big self-supervised models are strong semi-supervised learners

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.223962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1a0ec43a-297c-4ad1-90a0-8643f18e0011 · outbound

This paper cites PathNet: Evolution Channels Gradient Descent in Super Neural Networks.

Model Connectomes: A Generational Approach to Data-Efficient Language Models PathNet: Evolution Channels Gradient Descent in Super Neural Networks

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.277239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 498fad79-88e2-48e2-9db9-13097181a067 · outbound

This paper cites Learning both weights and connections for efficient neural networks.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Learning both weights and connections for efficient neural networks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.206720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b2d65e16-965c-4e69-8242-ef900970e782 · outbound

This paper cites Synaptic density in human frontal cortex-developmental changes and effects of aging.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Synaptic density in human frontal cortex-developmental changes and effects of aging

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.191754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d231055b-5c97-48a2-ae0b-bf09647f582e · outbound

This paper cites Natural evolution strategies.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Natural evolution strategies

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.151551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 03864042-9046-44fe-95e7-fb2588e7a8bf · outbound

This paper cites Designing neural net- works through neuroevolution.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Designing neural net- works through neuroevolution

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.058859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bc15e902-9dbb-420c-9e39-77a312046b0b · outbound

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

Model Connectomes: A Generational Approach to Data-Efficient Language Models Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.300110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ebb35a6-a31e-44d0-9d47-822635009f21 · outbound

This paper cites Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.354373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6006c113-686c-4909-a93f-494deca07ce9 · outbound

This paper cites Root mean square layer normalization, 2019.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Root mean square layer normalization, 2019

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:38.011109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b4fc5c3-6706-4a63-8a32-8f1bf7b9ab4a · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Roformer: Enhanced transformer with rotary position embedding

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:37.998646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5dac39b9-b80c-4afe-b805-c03c6a7d62cc · outbound

This paper cites Brain-score: Which artificial neural network for object recognition is most brain-like? BioRxiv, page 407007, 2018.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Brain-score: Which artificial neural network for object recognition is most brain-like? BioRxiv, page 407007, 2018

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:37.525087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9f64ae1-0113-4155-9db2-5230a2147c63 · outbound

This paper cites Hosseini, Nancy Kanwisher, Joshua B.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Hosseini, Nancy Kanwisher, Joshua B

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:38:37.975310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 84dcf064-9ca6-4074-9e11-4dc7cc52825a · outbound

This paper cites Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs.

Model Connectomes: A Generational Approach to Data-Efficient Language Models Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T05:38:36.776118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers