Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T11:33:18.712887Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2510.04500.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T11:33:18.712887Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
40 of 40 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 1c4b9164-73e9-48f1-bb6f-e7de55801d1b · outbound
Expand Neurons, Not Parameters On the complexity of neural computation in superposition
Reference 1
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Observation 4ecc8e7c-d5b2-40dd-9676-8c76e14d05a9 · outbound
Expand Neurons, Not Parameters Towards Combinatorial Interpretability of Neural Computation
Reference 2
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Observation f1225378-5451-420a-8113-7d8fec206700 · outbound
Expand Neurons, Not Parameters The lottery ticket hypothesis for pre-trained bert networks
Reference 3
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Observation 718f3f4c-8c46-4b19-92c9-40c5c9119760 · outbound
Expand Neurons, Not Parameters The lottery tickets hypothesis for supervised and self-supervised pre-training in computer vision models
Reference 4
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Observation 5086abc5-286b-4fa9-bde2-8334b87fcc53 · outbound
Expand Neurons, Not Parameters Net2Net: Accelerating Learning via Knowledge Transfer
Reference 5
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Observation bef8eab3-90ef-4aa0-a094-efdd1e716db2 · outbound
Expand Neurons, Not Parameters Imagenet: A large-scale hierarchical image database
Reference 6
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Observation fd391cb1-75bc-4d5a-a0bc-60b0708f1bda · outbound
Expand Neurons, Not Parameters Pure: Turning polysemantic neurons into pure features by identifying relevant circuits
Reference 7
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Observation a8d849f9-fcd8-4e34-884f-4fea884d1c69 · outbound
Reference 8
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Observation 969fb15b-01f2-45e4-8094-8dbce678d410 · outbound
Expand Neurons, Not Parameters Rigging the lottery: Making all tickets winners
Reference 9
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Observation 1d518cd7-da6e-44af-9ca1-a5f1dd62a5d1 · outbound
Expand Neurons, Not Parameters MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models
Reference 10
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Observation 5d03d10e-14a7-460b-a94f-2499c6fd9014 · outbound
Expand Neurons, Not Parameters The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Reference 11
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Observation f14b2c87-ade7-416b-9e06-52439f227372 · outbound
Expand Neurons, Not Parameters Sparsegpt: Massive language models can be accurately pruned in one-shot
Reference 12
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Observation 6fd936e0-445f-4980-8a79-c059e27133b6 · outbound
Expand Neurons, Not Parameters Multimodal neurons in artificial neural networks
Reference 13
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Observation 5ab5f514-f0e2-4fd7-a162-f630313c056d · outbound
Expand Neurons, Not Parameters Are wider nets better given the same number of parameters?
Reference 14
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Observation 54340b46-e7cd-436c-8ace-784b398c07b5 · outbound
Expand Neurons, Not Parameters Universal Neurons in GPT2 Language Models
Reference 15
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Observation b04190b8-67f7-40e5-852f-a6614060038e · outbound
Expand Neurons, Not Parameters Learning both weights and connections for efficient neural network
Reference 16
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Observation 1696d495-f987-4c85-86c1-f35dfdc58ce5 · outbound
Expand Neurons, Not Parameters Dynamic neural networks: A survey
Reference 17
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Observation 40ea786c-a2c5-4d8c-81d1-c329910fcffb · outbound
Expand Neurons, Not Parameters Mathematical Models of Computation in Superposition
Reference 18
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Observation eb4b2656-3cd9-446f-8c90-fc98628569a1 · outbound
Expand Neurons, Not Parameters Engineering Monosemanticity in Toy Models
Reference 19
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Observation f40b7283-0cfc-4739-a6f0-26d697aae671 · outbound
Expand Neurons, Not Parameters Learning multiple layers of features from tiny images
Reference 20
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Observation 16866f60-31c4-42d0-9da2-875eb330aa20 · outbound
Expand Neurons, Not Parameters What Causes Polysemanticity? An Alternative Origin Story of Mixed Selectivity from Incidental Causes
Reference 21
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Observation 13952b60-c9bd-40a8-aef1-1107bdc77dd9 · outbound
Expand Neurons, Not Parameters A Survey of Lottery Ticket Hypothesis
Reference 22
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Observation 1edc2362-95b0-4b44-bf94-b6241aeff5bf · outbound
Expand Neurons, Not Parameters Superposition Yields Robust Neural Scaling
Reference 23
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Observation 61cb87d9-b096-4f8f-a757-3996f5cf17d6 · outbound
Expand Neurons, Not Parameters Proving the lottery ticket hypothesis: Pruning is all you need
Reference 24
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Observation 3b6204f2-53a5-478b-baa9-c1f98cd05ad9 · outbound
Expand Neurons, Not Parameters Analysis of boolean functions
Reference 25
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Observation fc42be5c-6667-4136-8bd4-4e920162d553 · outbound
Expand Neurons, Not Parameters Zoom in: An introduction to circuits
Reference 26
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Observation 3fb9ff1c-6154-4124-acf8-ad77d0ea299f · outbound
Expand Neurons, Not Parameters Mixturegrowth: Growing neural networks by recombining learned parameters
Reference 27
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Observation 27f6956f-4b6b-4ac4-a88b-96f48c798b55 · outbound
Expand Neurons, Not Parameters Accelerating inference with sparsity using the nvidia ampere architecture and nvidia tensorrt
Reference 28
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Observation 9c3a1ff8-ae13-4c44-a857-61eea2e9d919 · outbound
Expand Neurons, Not Parameters Learning transferable visual models from natural language supervision
Reference 29
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Observation dd19aae6-2d35-4514-88d1-a725bd6b083a · outbound
Expand Neurons, Not Parameters Polysemanticity and Capacity in Neural Networks
Reference 30
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Observation ca2e2831-8dae-4016-b213-9f1d45f4f04e · outbound
Expand Neurons, Not Parameters A Simple and Effective Pruning Approach for Large Language Models
Reference 31
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Observation 38d47441-2ea0-460d-b855-7fd2b2c92273 · outbound
Expand Neurons, Not Parameters Firefly neural architecture descent: a general approach for growing neural networks
Reference 32
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Observation 2a288065-efe8-4b02-ad47-d4d8a6a54bbb · outbound
Expand Neurons, Not Parameters Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Reference 33
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Observation 1db67381-35de-408a-8c80-805b3d2c7aa8 · outbound
Expand Neurons, Not Parameters An effective gram matrix characterizes generalization in deep networks
Reference 34
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Observation 0bff169f-713c-4fec-b2ce-cf1dd358f694 · outbound
Expand Neurons, Not Parameters Growing Efficient Deep Networks by Structured Continuous Sparsification
Reference 35
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Observation e92a1b55-92f4-4007-8b67-faf1b59065f2 · outbound
Expand Neurons, Not Parameters Deconstructing lottery tickets: Zeros, signs, and the supermask
Reference 36
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Observation b6d2bd59-26b7-464b-88ac-838a4cd903ac · outbound
Expand Neurons, Not Parameters write newline
Reference 37
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Observation e40ee65a-09fd-490d-8334-2c982606a9f9 · outbound
Expand Neurons, Not Parameters @esa (Ref
Reference 38
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Observation 1452af98-d1e0-4ed1-8583-7018278cbc3e · outbound
Expand Neurons, Not Parameters Unresolved cited work
Reference 39
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Observation b671efc4-b48c-4af8-a11c-b06ce82ffb6a · outbound
Expand Neurons, Not Parameters I D ocٙ\^9;g=;;3g DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD suDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD䘘 TDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD &&
Reference 40
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No inbound Pith citation observations are available.