On the Fitness Landscape in the $NK$ Model | Paper Citation Record

Observation 97b9e8dc-42df-4d09-9191-65ebf5b6b459 · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer,.

On the Fitness Landscape in the $NK$ Model Outrageously large neural networks: The sparsely-gated mixture-of-experts layer,

Reference 1

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Observation 5fdf9f50-21bb-4d2e-b14b-b6ef90f9900b · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

On the Fitness Landscape in the $NK$ Model Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 2

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Observation 01e33fd6-5674-4d73-892c-b81251a3af00 · outbound

This paper cites Scaling Laws for Neural Language Models.

On the Fitness Landscape in the $NK$ Model Scaling Laws for Neural Language Models

Reference 3

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Observation c084eade-a9dd-4df5-b2a1-98bc6f5de8f9 · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

On the Fitness Landscape in the $NK$ Model Scaling Laws for Autoregressive Generative Modeling

Reference 4

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Observation 86f1ff89-0ed1-4d1b-994a-3e5ef3db8794 · outbound

This paper cites Training Compute-Optimal Large Language Models.

On the Fitness Landscape in the $NK$ Model Training Compute-Optimal Large Language Models

Reference 5

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Observation 93472440-9736-49b0-99e5-9774f0a45dc0 · outbound

This paper cites Language models are unsupervised multitask learners,.

On the Fitness Landscape in the $NK$ Model Language models are unsupervised multitask learners,

Reference 6

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Observation f87c0f81-4587-46d8-a766-c8651612e75e · outbound

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

On the Fitness Landscape in the $NK$ Model LLaMA: Open and Efficient Foundation Language Models

Reference 7

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Observation 14bb3d4d-0d0c-42ae-9da1-d9cc8172495f · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

On the Fitness Landscape in the $NK$ Model Gemma: Open Models Based on Gemini Research and Technology

Reference 8

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Observation a66a5f41-b482-4204-a87d-18da3d5aef53 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

On the Fitness Landscape in the $NK$ Model DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 9

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Observation 398b713d-089d-4cf6-9358-4ff3c2106742 · outbound

This paper cites Qwen Technical Report.

On the Fitness Landscape in the $NK$ Model Qwen Technical Report

Reference 10

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Observation 9d80a946-a444-4c70-8dba-26a5d59cd295 · outbound

This paper cites Qwen2.5-Coder Technical Report.

On the Fitness Landscape in the $NK$ Model Qwen2.5-Coder Technical Report

Reference 11

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Observation 79ca6084-7b31-4529-bdb9-1a71f628cb92 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

On the Fitness Landscape in the $NK$ Model Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 12

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Observation a2cb8270-120f-4bea-b3e1-a31a506fe875 · outbound

This paper cites Emergent Abilities of Large Language Models.

On the Fitness Landscape in the $NK$ Model Emergent Abilities of Large Language Models

Reference 13

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Observation c1609708-e906-4e27-a7f4-448625149cb8 · outbound

This paper cites Are emergent abilities of large language models a mirage?.

On the Fitness Landscape in the $NK$ Model Are emergent abilities of large language models a mirage?

Reference 14

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Observation 16b69d71-bf3f-45be-8d69-a4bb386b2615 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

On the Fitness Landscape in the $NK$ Model Measuring Massive Multitask Language Understanding

Reference 15

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Observation 00cde228-a824-4dec-8234-388682aaf51a · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

On the Fitness Landscape in the $NK$ Model Training Verifiers to Solve Math Word Problems

Reference 16

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Observation 7b2cea6b-c80c-41b6-8526-563358b52740 · outbound

This paper cites Solv- ing quantitative reasoning problems with language models,.

On the Fitness Landscape in the $NK$ Model Solv- ing quantitative reasoning problems with language models,

Reference 17

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Observation 4a98492a-965c-476b-a5d1-f72a4d64e084 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

On the Fitness Landscape in the $NK$ Model Evaluating Large Language Models Trained on Code

Reference 18

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Observation cd792c45-48f4-45f2-b3b0-ca6dfa14df96 · outbound

This paper cites Program Synthesis with Large Language Models.

On the Fitness Landscape in the $NK$ Model Program Synthesis with Large Language Models

Reference 19

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Observation 8db33f7f-9779-42b4-8872-d978ddd3b6b3 · outbound

This paper cites StarCoder: may the source be with you!.

On the Fitness Landscape in the $NK$ Model StarCoder: may the source be with you!

Reference 20

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Observation 97158e6d-4b9d-4596-b4e6-0b2cefd5fb31 · outbound

This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.

On the Fitness Landscape in the $NK$ Model CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 21

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Observation 95809443-76ae-4595-a8b3-2e20ee13fe0e · outbound

This paper cites InCoder: A Generative Model for Code Infilling and Synthesis.

On the Fitness Landscape in the $NK$ Model InCoder: A Generative Model for Code Infilling and Synthesis

Reference 22

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Observation 75f0976b-83a1-4bcf-b0f6-b0c2da178734 · outbound

This paper cites C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models,.

On the Fitness Landscape in the $NK$ Model C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models,

Reference 23

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Observation ee2571ad-d53e-4b78-aa7b-24129a356e18 · outbound

This paper cites Language Models are Few-shot Multilingual Learners.

On the Fitness Landscape in the $NK$ Model Language Models are Few-shot Multilingual Learners

Reference 24

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Observation d6e5a4c6-0f9c-453f-8cc9-def3a92072bf · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

On the Fitness Landscape in the $NK$ Model Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 25

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Observation 09d1d567-b669-4e90-b3d5-9b460052ffbd · outbound

This paper cites LaMDA: Language Models for Dialog Applications.

On the Fitness Landscape in the $NK$ Model LaMDA: Language Models for Dialog Applications

Reference 26

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Observation 9635f0e7-d019-4450-8577-68713deeb813 · outbound

This paper cites Recipes for building an open-domain chatbot.

On the Fitness Landscape in the $NK$ Model Recipes for building an open-domain chatbot

Reference 27

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Observation f0296b7b-8914-41fe-97eb-1e6ccce4435a · outbound

This paper cites Glam: Efficient scaling of language models with mixture-of-experts,.

On the Fitness Landscape in the $NK$ Model Glam: Efficient scaling of language models with mixture-of-experts,

Reference 28

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Observation a4184f89-b5e9-437e-9ebc-2bd763d30caa · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

On the Fitness Landscape in the $NK$ Model Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 29

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Observation 47e4f7dc-5113-4cc3-b083-c681add78bde · outbound

This paper cites Efficient Large Scale Language Modeling with Mixtures of Experts.

On the Fitness Landscape in the $NK$ Model Efficient Large Scale Language Modeling with Mixtures of Experts

Reference 30

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This paper cites Mixture-of-experts with expert choice routing,.

On the Fitness Landscape in the $NK$ Model Mixture-of-experts with expert choice routing,

Reference 31

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

On the Fitness Landscape in the $NK$ Model Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 32

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Observation 88b9bf59-3e33-4421-9a6a-64b45d694e12 · outbound

This paper cites The Falcon Series of Open Language Models.

On the Fitness Landscape in the $NK$ Model The Falcon Series of Open Language Models

Reference 33

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Observation 4994c5ff-afda-49f2-b967-6186bd35d024 · outbound

This paper cites Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale,.

On the Fitness Landscape in the $NK$ Model Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale,

Reference 34

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This paper cites On the Opportunities and Risks of Foundation Models.

On the Fitness Landscape in the $NK$ Model On the Opportunities and Risks of Foundation Models

Reference 35

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On the Fitness Landscape in the $NK$ Model Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 36

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On the Fitness Landscape in the $NK$ Model (2025) Claude opus 4.1

Reference 37

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On the Fitness Landscape in the $NK$ Model Qwen3 Technical Report

Reference 38

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On the Fitness Landscape in the $NK$ Model Unresolved cited work

Reference 39

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On the Fitness Landscape in the $NK$ Model Eight Things to Know about Large Language Models

Reference 40

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On the Fitness Landscape in the $NK$ Model AI and the Everything in the Whole Wide World Benchmark

Reference 41

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On the Fitness Landscape in the $NK$ Model Holistic evaluation of language models,

Reference 42

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On the Fitness Landscape in the $NK$ Model With little power comes great responsibility,

Reference 43

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On the Fitness Landscape in the $NK$ Model NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark

Reference 44

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On the Fitness Landscape in the $NK$ Model A Survey of Large Language Models

Reference 45

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On the Fitness Landscape in the $NK$ Model Large Language Models: A Survey

Reference 46

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On the Fitness Landscape in the $NK$ Model llama.cpp: Inference of llama model in pure c/c++,

Reference 47

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Observation ca137c25-3508-464f-bf40-f920f2ac3237 · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

On the Fitness Landscape in the $NK$ Model GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 48

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On the Fitness Landscape in the $NK$ Model Attention is all you need,

Reference 49

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On the Fitness Landscape in the $NK$ Model Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 50

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On the Fitness Landscape in the $NK$ Model PaLM: Scaling Language Modeling with Pathways

Reference 51

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Observation 46faadb0-3890-410f-9c62-49a315785d81 · outbound

This paper cites FinQA: A Dataset of Numerical Reasoning over Financial Data.

On the Fitness Landscape in the $NK$ Model FinQA: A Dataset of Numerical Reasoning over Financial Data

Reference 52

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Observation 5351e94d-c534-4f21-8f9c-99225dbe4602 · outbound

This paper cites Medical Exam Question Answering with Large-scale Reading Comprehension.

On the Fitness Landscape in the $NK$ Model Medical Exam Question Answering with Large-scale Reading Comprehension

Reference 53

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Observation 5b6a6641-b714-4a82-b1c7-a196f8a5cd9e · outbound

This paper cites Experimenting with Legal AI Solutions: The Case of Question-Answering for Access to Justice.

On the Fitness Landscape in the $NK$ Model Experimenting with Legal AI Solutions: The Case of Question-Answering for Access to Justice

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:29:01.864173Z

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Observation 6235c2ca-f238-4fb6-9aeb-7ed010218188 · outbound

This paper cites Crowdsourcing multiple choice science questions,.

On the Fitness Landscape in the $NK$ Model Crowdsourcing multiple choice science questions,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:07.160436Z

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Observation 382bea05-8712-4b3c-bb58-4ba30b929ee3 · outbound

This paper cites PIQA: Reasoning about Physical Commonsense in Natural Language.

On the Fitness Landscape in the $NK$ Model PIQA: Reasoning about Physical Commonsense in Natural Language

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:56.079598Z

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Observation 2ea4ea9b-4b82-47a9-8014-ff83dd2b970c · outbound

This paper cites DialogSum: A Real-Life Scenario Dialogue Summarization Dataset.

On the Fitness Landscape in the $NK$ Model DialogSum: A Real-Life Scenario Dialogue Summarization Dataset

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:56.205859Z

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Observation 33f5d483-b044-4206-ae68-1e7339a9b9a8 · outbound

This paper cites Xtreme: A massively multilingual multi-task benchmark for evaluat- ing cross-lingual generalisation,.

On the Fitness Landscape in the $NK$ Model Xtreme: A massively multilingual multi-task benchmark for evaluat- ing cross-lingual generalisation,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:06.957523Z

Source-reported events for the cited work

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Observation b35d30f8-26c7-45d1-8471-6fe81b10b6dd · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

On the Fitness Landscape in the $NK$ Model mT5: A massively multilingual pre-trained text-to-text transformer

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:56.406142Z

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Observation e30c118b-69cd-4b7c-8904-701373841398 · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

On the Fitness Landscape in the $NK$ Model Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:56.492871Z

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Observation a2be7f89-a0e7-4603-94c7-fa9a0b8d0429 · outbound

This paper cites Language mod- els are few-shot learners,.

On the Fitness Landscape in the $NK$ Model Language mod- els are few-shot learners,

Reference 61

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Observation af4e531f-be73-41e2-9f3d-79f51b3f283f · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

On the Fitness Landscape in the $NK$ Model Chain-of-thought prompting elicits reasoning in large language models,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:56.738370Z

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Observation 90d9badf-3d65-4be4-b62e-6d6c064f85c4 · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

On the Fitness Landscape in the $NK$ Model Large lan- guage models are zero-shot reasoners,

Reference 63

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Observation 01e76e6f-6c0f-4da1-ab45-8f93df314c62 · outbound

This paper cites Large Language Models are not Fair Evaluators.

On the Fitness Landscape in the $NK$ Model Large Language Models are not Fair Evaluators

Reference 64

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Observation 97985d9e-c582-43aa-abcf-429a4f47a9c3 · outbound

This paper cites The Curious Case of Neural Text Degeneration.

On the Fitness Landscape in the $NK$ Model The Curious Case of Neural Text Degeneration

Reference 65

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Observation 3944346b-d07f-4888-b30a-eef52552b6c0 · outbound

This paper cites Neural Text Generation with Unlikelihood Training.

On the Fitness Landscape in the $NK$ Model Neural Text Generation with Unlikelihood Training

Reference 66

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Observation cf99bc11-3a69-4916-97fa-e214337d76dc · outbound

This paper cites The goldilocks of pragmatic understanding: Fine-tuning strategy matters for implicature resolution by llms,.

On the Fitness Landscape in the $NK$ Model The goldilocks of pragmatic understanding: Fine-tuning strategy matters for implicature resolution by llms,

Reference 67

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Observation 7085bb93-5209-4e02-b1a1-246a440967c7 · outbound

This paper cites Locally typical sampling,.

On the Fitness Landscape in the $NK$ Model Locally typical sampling,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:06.487349Z

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Observation aacb67d3-838c-4261-8365-ac1b16ec12f6 · outbound

This paper cites The hitchhiker’s guide to testing statistical significance in natural language processing,.

On the Fitness Landscape in the $NK$ Model The hitchhiker’s guide to testing statistical significance in natural language processing,

Reference 69

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Observation 067d6de7-a91b-40b1-b106-5fdb24a8930c · outbound

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On the Fitness Landscape in the $NK$ Model Note on the sampling error of the difference between correlated proportions or percentages,

Reference 70

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On the Fitness Landscape in the $NK$ Model Controlling the false discovery rate: a practical and powerful approach to multiple testing,

Reference 71

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On the Fitness Landscape in the $NK$ Model Cohen,Statistical power analysis for the behavioral sciences

Reference 72

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On the Fitness Landscape in the $NK$ Model Efron and R

Reference 73

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Observation 3b31a3b1-d231-4c9f-a326-ea1487a1027d · outbound

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On the Fitness Landscape in the $NK$ Model Statistical significance tests for machine translation evalua- tion,

Reference 74

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Observation 33828057-5fa6-4141-a3db-14c06fe9e1e3 · outbound

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On the Fitness Landscape in the $NK$ Model Information-Theoretic Probing for Linguistic Structure

Reference 75

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Observation f9845ccf-8fed-40b6-87ad-b7a7eabef09d · outbound

This paper cites A statistical analysis of summariza- tion evaluation metrics using resampling methods,.

On the Fitness Landscape in the $NK$ Model A statistical analysis of summariza- tion evaluation metrics using resampling methods,

Reference 76

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Observation 63eda27d-079d-4bdc-a390-2353b5ea48da · outbound

This paper cites Improving reproducibility in machine learning research: a report from the neurips 2019 reproducibil- ity program,.

On the Fitness Landscape in the $NK$ Model Improving reproducibility in machine learning research: a report from the neurips 2019 reproducibil- ity program,

Reference 77

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On the Fitness Landscape in the $NK$ Model Show your work: Improved reporting of experimental results,

Reference 78

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Observation 39b581f4-7ad5-4d0a-a2c8-362ba50e06d3 · outbound

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On the Fitness Landscape in the $NK$ Model Data Contamination: From Memorization to Exploitation

Reference 79

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Observation cab6cc4e-b85f-4474-a1cf-37662617ef60 · outbound

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On the Fitness Landscape in the $NK$ Model A Comparative Analysis of Counterfactual Explanation Methods for Text Classifiers

Reference 80

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Observation ad697f95-89ee-486a-8cab-5081759d89ab · outbound

This paper cites Inverse scaling can become U-shaped.

On the Fitness Landscape in the $NK$ Model Inverse scaling can become U-shaped

Reference 81

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Observation 7b3d9530-2f85-41c7-a555-20bda3ccf042 · outbound

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On the Fitness Landscape in the $NK$ Model Inverse Scaling: When Bigger Isn't Better

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:59.286934Z

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On the Fitness Landscape in the $NK$ Model Predictability and surprise in large generative models,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:04.640494Z

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Observation 7a4cfab5-5304-4c50-b958-c5bf2649b01e · outbound

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On the Fitness Landscape in the $NK$ Model Large language models struggle to learn long-tail knowledge,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:04.370661Z

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Observation 41b0d380-9a7f-4e46-a769-e02400c748fe · outbound

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On the Fitness Landscape in the $NK$ Model Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 85

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On the Fitness Landscape in the $NK$ Model Rethink reporting of evaluation results in ai,

Reference 86

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On the Fitness Landscape in the $NK$ Model Impact of Pretraining Term Frequencies on Few-Shot Reasoning

Reference 87

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On the Fitness Landscape in the $NK$ Model A systematic evaluation of large language models of code,

Reference 88

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This paper cites Energy and policy consider- ations for deep learning in nlp,.

On the Fitness Landscape in the $NK$ Model Energy and policy consider- ations for deep learning in nlp,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:03.682308Z

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Observation 838a3295-8026-465a-9541-bf502a8a9bf7 · outbound

This paper cites Carbon Emissions and Large Neural Network Training.

On the Fitness Landscape in the $NK$ Model Carbon Emissions and Large Neural Network Training

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-05T19:29:00.268605Z

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Observation 080ef9b7-cddb-4152-bcc5-4922789c9383 · outbound

This paper cites Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers.

On the Fitness Landscape in the $NK$ Model Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers

Reference 91

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Observation db3810a4-9dfd-450d-b908-09111932e80c · outbound

This paper cites Teoria statistica delle classi e calcolo delle probabilita,.

On the Fitness Landscape in the $NK$ Model Teoria statistica delle classi e calcolo delle probabilita,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:03.416842Z

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This paper cites New effect size rules of thumb,.

On the Fitness Landscape in the $NK$ Model New effect size rules of thumb,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:29:03.214323Z

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Observation f604fc2f-c03b-487d-bca8-b2bc4554d690 · outbound

This paper cites The measurement of observer agreement for categorical data,.

On the Fitness Landscape in the $NK$ Model The measurement of observer agreement for categorical data,

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-05T19:29:00.825639Z

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Observation 9cacb826-2b11-4a98-a8fe-18037959b7c0 · outbound

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On the Fitness Landscape in the $NK$ Model Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

Reference 95

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