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Paper Citation Record · LEDGER

LEMUR 2: Unlocking Neural Network Diversity for AI

As of 6 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2607.06839.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.06839 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T20:15:59.064352Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

52 of 52 outbound references displayed

  • verified exact19
  • verified fuzzy28
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 60c4e56a-19e6-42b5-a68b-27dc8e1d7f6b · outbound

This paper cites AugmentGest: Can Random Data Cropping Augmentation Boost Gesture Recognition Performance?.

LEMUR 2: Unlocking Neural Network Diversity for AI AugmentGest: Can Random Data Cropping Augmentation Boost Gesture Recognition Performance?

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 8d4fd9c4-3e1b-4c9e-8f31-f4c9535cb698 · outbound

This paper cites Jahs-bench-201: A foundation for research on joint architecture and hyperparameter search.

LEMUR 2: Unlocking Neural Network Diversity for AI Jahs-bench-201: A foundation for research on joint architecture and hyperparameter search

Reference 2

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raw_fallback, observed 2026-07-10T20:17:33.950985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4ae1f3f3-49c9-4f5d-924c-d71d19390e44 · outbound

This paper cites Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet.

LEMUR 2: Unlocking Neural Network Diversity for AI Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet

Reference 3

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local_arxiv, observed 2026-07-10T20:17:33.753607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 42a6271a-b0dc-4295-be47-4b57076a1380 · outbound

This paper cites AIRNet: Self-Supervised Affine Registration for 3D Medical Images using Neural Networks.

LEMUR 2: Unlocking Neural Network Diversity for AI AIRNet: Self-Supervised Affine Registration for 3D Medical Images using Neural Networks

Reference 4

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local_arxiv, observed 2026-07-10T20:17:33.761948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:f8cf61b7160be73305eb51bf299e6f19d9661feb5e6e1414aef60235a7e74232

Observation 783a084b-90c4-4b15-9b85-d57f26f6abf3 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

LEMUR 2: Unlocking Neural Network Diversity for AI Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 5

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local_arxiv, observed 2026-07-10T20:17:33.748304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:e24f71b7015d9cf6a93c50927cb160e0cac06b103918375cfa470303cd1a2098

Observation 8202802b-87b1-4c9c-acc2-83a2221cc9f0 · outbound

This paper cites Ai on the edge: An automated pipeline for pytorch-to-android deployment and benchmarking.Preprints, 2025.

LEMUR 2: Unlocking Neural Network Diversity for AI Ai on the edge: An automated pipeline for pytorch-to-android deployment and benchmarking.Preprints, 2025

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:1ffacbaa59fa676916a02cc9e1379bf0eec0b87d8cdb08f929a44f8c5657da1b

Observation 1792de37-29ac-44d8-9aea-d1d64645c361 · outbound

This paper cites NAS-Bench-201: Extending the scope of reproducible neural architecture search.

LEMUR 2: Unlocking Neural Network Diversity for AI NAS-Bench-201: Extending the scope of reproducible neural architecture search

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:1c6dbe48ddf696ad20236337834d69888799dc52874189c699b5c88f475441bc

Observation cb3a2cf2-2b39-4a74-bba4-bb163d041c97 · outbound

This paper cites NATS-Bench: Benchmarking nas algorithms for ar- chitecture topology and size.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.

LEMUR 2: Unlocking Neural Network Diversity for AI NATS-Bench: Benchmarking nas algorithms for ar- chitecture topology and size.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

Reference 8

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arxiv_id, observed 2026-07-10T20:17:33.742704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:420cc28d5fb1b7fddadf9f6cd6c8faafb8c967a85d6779f06ddc806a25ce209c

Observation 3f9ee8e2-a96c-4512-9e80-a559d5897e77 · outbound

This paper cites Transnas-bench-101: Improving transferability and generalizability of cross-task neural architecture search.

LEMUR 2: Unlocking Neural Network Diversity for AI Transnas-bench-101: Improving transferability and generalizability of cross-task neural architecture search

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation d3f81cb5-04b2-4a35-ab39-035825ad0d45 · outbound

This paper cites an unresolved cited work.

LEMUR 2: Unlocking Neural Network Diversity for AI Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4d27a94f-265d-4f94-9c62-445443c8b3b1 · outbound

This paper cites NNGPT: Rethinking AutoML with Large Language Models.

LEMUR 2: Unlocking Neural Network Diversity for AI NNGPT: Rethinking AutoML with Large Language Models

Reference 11

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local_arxiv, observed 2026-07-10T20:17:33.765979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation d9abff4b-e19c-470e-a118-dbc2edfa242f · outbound

This paper cites A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks.

LEMUR 2: Unlocking Neural Network Diversity for AI A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks

Reference 12

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local_arxiv, observed 2026-07-10T20:17:33.745309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 9472f5aa-ab29-43d6-8d85-318c1460fb2d · outbound

This paper cites From Memorization to Creativity: LLM as a Designer of Novel Neural Architectures.

LEMUR 2: Unlocking Neural Network Diversity for AI From Memorization to Creativity: LLM as a Designer of Novel Neural Architectures

Reference 13

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local_arxiv, observed 2026-07-10T20:17:33.760735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:6f7373038d35b077c9b0d2762086545edcbe4188238090fa14832587816e59d2

Observation 7eaa31c1-b8bb-450a-9d45-ba4591770b32 · outbound

This paper cites VIST-GPT: Ushering in the Era of Visual Storytelling with LLMs?.

LEMUR 2: Unlocking Neural Network Diversity for AI VIST-GPT: Ushering in the Era of Visual Storytelling with LLMs?

Reference 14

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local_arxiv, observed 2026-07-10T20:17:33.742935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:44ad8a01fa1f23ca069d4320ecfb7f1254743cc8d17512b99801f5ca54059707

Observation 3a432504-2816-434f-b37b-beebccfafd4d · outbound

This paper cites LEMUR Neural Network Dataset: Towards Seamless AutoML, 2025.

LEMUR 2: Unlocking Neural Network Diversity for AI LEMUR Neural Network Dataset: Towards Seamless AutoML, 2025

Reference 15

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raw_fallback, observed 2026-07-10T20:17:33.952509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:fd9f2242383c31ec1bb9604d74468388cbd6902892e1a46d896cc4753f0fb250

Observation b0c98cda-ad26-4fad-af1a-29a09a62f7ca · outbound

This paper cites Tensorflow hub.https://www.tensorflow.

LEMUR 2: Unlocking Neural Network Diversity for AI Tensorflow hub.https://www.tensorflow

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 2b07cdb2-1391-4417-af53-5b542e1b777a · outbound

This paper cites Resource- efficient iterative LLM-based NAS with feedback memory.

LEMUR 2: Unlocking Neural Network Diversity for AI Resource- efficient iterative LLM-based NAS with feedback memory

Reference 17

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arxiv_id, observed 2026-07-10T20:17:33.759428Z

Source-reported events for the cited work

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Observation 807256e4-69b1-4fdc-9186-9845ea8f549e · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851.

LEMUR 2: Unlocking Neural Network Diversity for AI Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:bb0d8f6699c7dfff8e16a8a33e421894b7214cd2aa660b6e5f398f7969549097

Observation df278580-9b97-4cbb-87b6-9734c8d9a8a8 · outbound

This paper cites Long short-term memory.Neural Computation, 9(8):1735–1780.

LEMUR 2: Unlocking Neural Network Diversity for AI Long short-term memory.Neural Computation, 9(8):1735–1780

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 90b225dc-4e0a-4fdf-9ff3-1fe6d1390c93 · outbound

This paper cites Densely connected convolutional net- works.

LEMUR 2: Unlocking Neural Network Diversity for AI Densely connected convolutional net- works

Reference 20

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 387c9f6b-651a-4ac4-ab05-079a61d17d43 · outbound

This paper cites Llm as a neural architect: Controlled generation of image cap- tioning models under strict api contracts.

LEMUR 2: Unlocking Neural Network Diversity for AI Llm as a neural architect: Controlled generation of image cap- tioning models under strict api contracts

Reference 21

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arxiv_id, observed 2026-07-10T20:17:33.737815Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation a1c55ead-b8cf-4bfa-9df6-14da6cf98912 · outbound

This paper cites Auto-keras: An efficient neural architecture search system.

LEMUR 2: Unlocking Neural Network Diversity for AI Auto-keras: An efficient neural architecture search system

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:2884f6fec69e4385620dfc8250b13383bf3b4a4e29cef7deaee76dad5cdd9808

Observation 38253b83-4651-427e-98d2-24d6dd627a47 · outbound

This paper cites Auto-Encoding Variational Bayes.

LEMUR 2: Unlocking Neural Network Diversity for AI Auto-Encoding Variational Bayes

Reference 23

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local_arxiv, observed 2026-07-10T20:17:33.764290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:133f48328c643fe9c1def4f301d96eeab336ec7edbb33d379148d753cbb3ee51

Observation e256beaf-a7ec-4deb-835e-37b046641c1a · outbound

This paper cites Nas-bench-nlp: neural architecture search benchmark for natural language processing.IEEE Access, 10:45736–45747, 2022.

LEMUR 2: Unlocking Neural Network Diversity for AI Nas-bench-nlp: neural architecture search benchmark for natural language processing.IEEE Access, 10:45736–45747, 2022

Reference 24

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Observation 1e4f28ee-401d-413d-8c4b-4726310199e4 · outbound

This paper cites an unresolved cited work.

LEMUR 2: Unlocking Neural Network Diversity for AI Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4b9712bb-e0bf-440d-b4c3-187dc86b1a8c · outbound

This paper cites Learning multiple layers of features from tiny images.

LEMUR 2: Unlocking Neural Network Diversity for AI Learning multiple layers of features from tiny images

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5092b920-8d45-43ff-8fce-4da5b90b1c0c · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

LEMUR 2: Unlocking Neural Network Diversity for AI Imagenet classification with deep convolutional neural net- works

Reference 27

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raw_fallback, observed 2026-07-10T20:17:33.966590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 6264cee8-3311-482d-995b-d116e9b116df · outbound

This paper cites FractalNet: Ultra-Deep Neural Networks without Residuals.

LEMUR 2: Unlocking Neural Network Diversity for AI FractalNet: Ultra-Deep Neural Networks without Residuals

Reference 28

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local_arxiv, observed 2026-07-10T20:17:33.751401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation db9032ed-b73b-4236-b099-b4eebdade8d7 · outbound

This paper cites HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark.

LEMUR 2: Unlocking Neural Network Diversity for AI HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

Reference 29

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local_arxiv, observed 2026-07-10T20:17:33.769429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:badabd2c068559bd7ab801230c950683f8fa44571ca522f2775c18b2f4dc3987

Observation d8820d97-0779-48b4-8b11-c070f396d382 · outbound

This paper cites LibCST: A concrete syntax tree parser and serializer library for python.https://github.

LEMUR 2: Unlocking Neural Network Diversity for AI LibCST: A concrete syntax tree parser and serializer library for python.https://github

Reference 30

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raw_fallback, observed 2026-07-10T20:17:33.966789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:280fafa98d8fcf01144290a1ec0e2721c6aee773194e12fc25a5399af38a195d

Observation d32d8ae0-161c-4e67-8e82-2ff0fd8bc160 · outbound

This paper cites Microsoft coco: Common objects in context.

LEMUR 2: Unlocking Neural Network Diversity for AI Microsoft coco: Common objects in context

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 621c5d73-a5dc-4ac6-a604-22a5443bae22 · outbound

This paper cites Nas-bench-asr: Reproducible neural architecture search for speech recogni- tion.

LEMUR 2: Unlocking Neural Network Diversity for AI Nas-bench-asr: Reproducible neural architecture search for speech recogni- tion

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:08c36af227026d4b8923d9c63ae8df1c419dc21eb9fc595c875cbb8d11c3b830

Observation 5e70a302-46e2-40a2-adb4-e19d21d39756 · outbound

This paper cites Preparation of Fractal-Inspired Computational Architectures for Advanced Large Language Model Analysis.

LEMUR 2: Unlocking Neural Network Diversity for AI Preparation of Fractal-Inspired Computational Architectures for Advanced Large Language Model Analysis

Reference 33

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local_arxiv, observed 2026-07-10T20:17:33.771904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:4185cf6495691b2008c0f56047ff1be5b6ba3b5480d6f51dd0569816ad0d95dd

Observation ca52e3d5-7962-44ed-98da-aa6ef0ee2c60 · outbound

This paper cites Olson and Jason H.

LEMUR 2: Unlocking Neural Network Diversity for AI Olson and Jason H

Reference 34

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raw_fallback, observed 2026-07-10T20:17:33.938524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:31dec116bd93ff5338542bf2af97c4b3fdf0a3a3ba9bf737e85379ca1ae809e5

Observation d623a3ed-5cda-468d-98e9-01d325d3fdfb · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

LEMUR 2: Unlocking Neural Network Diversity for AI Bleu: a method for automatic evaluation of machine translation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.932307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:6ab7611a68e30d2f716792718bc5ff1416d025e9c7cde7a37adb36035d28e815

Observation 96607348-927f-4989-8255-8c58df015332 · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library, 2019.

LEMUR 2: Unlocking Neural Network Diversity for AI Pytorch: An im- perative style, high-performance deep learning library, 2019

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.936454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:ed1ab9daf808c926164c1005f9041f31e3f03d142fdd3c04cdf3346704f9d5ec

Observation 4efebd1d-2a99-4456-86c7-58edc9ac4cc1 · outbound

This paper cites Pytorch hub.https://pytorch.

LEMUR 2: Unlocking Neural Network Diversity for AI Pytorch hub.https://pytorch

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.940037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:1662271d35f9c05bbf5e690a8cbc830602e8803b8b7000153a0bbf02ecdae226

Observation 1c303767-b633-4022-abd1-067819c0667e · outbound

This paper cites Nas-bench-graph: Benchmarking graph neural architecture search.Advances in neural information process- ing systems, 35:54–69, 2022.

LEMUR 2: Unlocking Neural Network Diversity for AI Nas-bench-graph: Benchmarking graph neural architecture search.Advances in neural information process- ing systems, 35:54–69, 2022

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.930420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:1b2446b02567a79402e5fc2015a793d7b17e59460f5fd85847df972d8847da8f

Observation d52a994f-32b1-48aa-9a02-a59617d7e4ea · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

LEMUR 2: Unlocking Neural Network Diversity for AI Learning transferable visual models from natural language supervi- sion

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.932512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:4b2c10e938f4430999cb6561d368f38472f70c22d1d7209d77ff605635f8729c

Observation 4e191a86-c823-4f84-b675-50f5a7b3ac3d · outbound

This paper cites an unresolved cited work.

LEMUR 2: Unlocking Neural Network Diversity for AI Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:17:33.944438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:54493f7bf9c24ba4351a8b2ed7f312dfcbc5961b7b5375f9c89ec4f1bcb79fdc

Observation de4ca4ba-d4e2-4701-9c00-d50a46f90ef3 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

LEMUR 2: Unlocking Neural Network Diversity for AI High-resolution image synthesis with latent diffusion models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.962200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:cae3f4365aa4099fd90ff3de8dd44df657a8515cb88ee55d73b03b40dfc3c664

Observation c244845e-e8ee-4b13-9e53-d3c2a4799806 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

LEMUR 2: Unlocking Neural Network Diversity for AI U- net: Convolutional networks for biomedical image segmen- tation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.964103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:05a25b732e0c37bb6108b161d2f28864465f1e2401c250d4b6a3f910024e0b8f

Observation 3613cab3-4d10-447c-b0f5-a89ec171c173 · outbound

This paper cites Ex- ploring the collaboration between vision models and llms for enhanced image classification.Dimensions, 27(1), 2025.

LEMUR 2: Unlocking Neural Network Diversity for AI Ex- ploring the collaboration between vision models and llms for enhanced image classification.Dimensions, 27(1), 2025

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-10T20:17:33.488100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:60d2e1cc4eb3234c0ec962c3fdb285b7064002c629060dbd2caec28dd0f932f4

Observation d520a1c8-fc25-46bf-9fcc-530262caa103 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

LEMUR 2: Unlocking Neural Network Diversity for AI DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-07-10T20:17:33.740513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:72fb3b0fee578e10c5ed1ade8afc0cdc9958483cf01f85dff98673e7ebd39c93

Observation 0a8b1f82-023a-4ff5-b556-55d017c617c8 · outbound

This paper cites From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs.

LEMUR 2: Unlocking Neural Network Diversity for AI From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-08-06T02:01:35.592368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:fa5381207f695f454bdd7f3a164b6f114e62dcdda0a6fe4204a642e67544031a

Observation 60e4be64-41c6-483a-94f1-9b96363c230e · outbound

This paper cites Nas-bench-301 and the case for surrogate benchmarks for neural architecture search.

LEMUR 2: Unlocking Neural Network Diversity for AI Nas-bench-301 and the case for surrogate benchmarks for neural architecture search

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.960182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:6780c77723dfdd80225c73c73fd01e688438e6c4a068f0d3fde9976ef2ee8558

Observation d6d6f226-fdaa-4dc0-94e5-5a8131383678 · outbound

This paper cites Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models.

LEMUR 2: Unlocking Neural Network Diversity for AI Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-07-10T20:17:33.748026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:c76d57e0be35422efd6a3843fe01d2fe9864933c7a4114b726c4b9fbd9e132fd

Observation 777ab08a-3b77-4fe5-8878-5874d64f56e8 · outbound

This paper cites Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design.

LEMUR 2: Unlocking Neural Network Diversity for AI Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-07-10T20:17:33.736738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:f7299a6dbab22d267f920d9ff89c19138ce3715d0671589fa06698d7a0977398

Observation 92cde3f4-81a5-47f7-ab34-6a1da525604b · outbound

This paper cites an unresolved cited work.

LEMUR 2: Unlocking Neural Network Diversity for AI Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:17:33.956019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:7ee0453dcd4320c0d2f19c72c852f3af74e93345e9d45ab34402d5347d829304

Observation 42cb51e1-6ede-467f-a2d4-a6f1e72888ac · outbound

This paper cites Nas-bench-101: Towards reproducible neural architecture search.

LEMUR 2: Unlocking Neural Network Diversity for AI Nas-bench-101: Towards reproducible neural architecture search

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.948628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:972fb6f4e48b9122351dbcc5bf0f6d68368a9ba94fdb60d6f162db908888822c

Observation d8587ec3-574a-4e3f-92eb-fde70e39fc0a · outbound

This paper cites Nas-bench- 1shot1: Benchmarking and dissecting one-shot neural archi- tecture search.

LEMUR 2: Unlocking Neural Network Diversity for AI Nas-bench- 1shot1: Benchmarking and dissecting one-shot neural archi- tecture search

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.950505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:724b40df9138887d0f99f220357aaad04804c07d5beb6436a64f79d676e97b2a

Observation dafd2f37-f33e-4734-96bd-281ccf55e770 · outbound

This paper cites Self-attention generative adversarial networks.

LEMUR 2: Unlocking Neural Network Diversity for AI Self-attention generative adversarial networks

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:17:33.946561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-10T20:15:59.064352Z digest=sha256:205a71b7dfa2d8cb396d707a829bedf8c76596ea7658b1236d371344ccbbe807

Pith citing papers

No inbound Pith citation observations are available.