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Paper Citation Record · LEDGER

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation

As of 10 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2607.23860.

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

pith.paper-citation-record.v1
2607.23860 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T14:07:56.773429Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

17 of 17 outbound references displayed

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External citation measurements

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Outbound references

Observation a3275cd9-e7b9-49c0-bae8-7e0483e74ff6 · outbound

This paper cites Fix one feature in one regularised layer and letsm =σ(γ m)∈(0,1)be memberm’s importance for it, with across-member sharesp= softmax τ(s).

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Fix one feature in one regularised layer and letsm =σ(γ m)∈(0,1)be memberm’s importance for it, with across-member sharesp= softmax τ(s)

Reference 1

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Observation d06c4069-1f30-45ea-83b8-6c9879a09d76 · outbound

This paper cites Columns:τ= 0.1(left), τ= 1(right).

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Columns:τ= 0.1(left), τ= 1(right)

Reference 4

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Observation 69ae46c6-26cd-4ebb-b005-4b39a681addf · outbound

This paper cites Improving robustness and calibration in ensembles with diversity regularization.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Improving robustness and calibration in ensembles with diversity regularization

Reference 6

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Observation d523a097-fc51-4f8e-ab10-d3faea0282de · outbound

This paper cites Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks

Reference 7

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Observation bf2f3edd-265d-47c7-b5b7-f874e768427c · outbound

This paper cites Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, and Benjamin Van Roy.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, and Benjamin Van Roy

Reference 8

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Observation ba45b1ed-e4f5-4493-8b6a-d711323d5491 · outbound

This paper cites The two agree on the setting and differ in how member diversity is produced, how the modulation is parameterised, and how it is optimised.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation The two agree on the setting and differ in how member diversity is produced, how the modulation is parameterised, and how it is optimised

Reference 13

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Observation 38f212c4-e726-428e-a61c-406a5ebf2996 · outbound

This paper cites Member heads are reinitialised: a shared head is a symmetric fixed point at which the regulariser has no gradient, so reinitialisation supplies the asymmetry the mechanism needs.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Member heads are reinitialised: a shared head is a symmetric fixed point at which the regulariser has no gradient, so reinitialisation supplies the asymmetry the mechanism needs

Reference 14

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Observation 94ebb6e4-1723-407c-ab10-5217d3e21cc8 · outbound

This paper cites Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles

Reference 2013

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Observation 717e9943-b88b-49f5-bb0b-211d8cbded20 · outbound

This paper cites Is BatchEnsemble a single model? on calibration and diversity of efficient ensembles.arXiv preprint arXiv:2601.16936,.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Is BatchEnsemble a single model? on calibration and diversity of efficient ensembles.arXiv preprint arXiv:2601.16936,

Reference 2016

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Observation bf6ae077-00f9-4989-bb88-ba12058fc66d · outbound

This paper cites •Geometric ambiguity(output-space, label-free): the ambiguity term under the cross-entropy’s centroid combiner, the normalised geometric mean (Wood et al., 2023).

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation •Geometric ambiguity(output-space, label-free): the ambiguity term under the cross-entropy’s centroid combiner, the normalised geometric mean (Wood et al., 2023)

Reference 2018

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Observation 8c985520-381f-47b1-9c73-8cf0ff8826bf · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Distilling the Knowledge in a Neural Network

Reference 2019

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Observation e78b1a56-b51c-437e-bb39-20b28306ffd0 · outbound

This paper cites Receding Neuron Importances for Structured Pruning.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Receding Neuron Importances for Structured Pruning

Reference 2020

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Observation e6e3e9e6-243e-4bce-b7ac-86596792d8b8 · outbound

This paper cites Deep Ensembles: A Loss Landscape Perspective.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Deep Ensembles: A Loss Landscape Perspective

Reference 2022

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Observation 170b5c24-44fe-4ff2-8dbd-5d1ef0134aaa · outbound

This paper cites A Survey of Uncertainty in Deep Neural Networks.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation A Survey of Uncertainty in Deep Neural Networks

Reference 2023

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Observation 4222722e-09c1-413b-8908-6a47f4622716 · outbound

This paper cites Ensembling Pruned Attention Heads For Uncertainty-Aware Efficient Transformers.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Ensembling Pruned Attention Heads For Uncertainty-Aware Efficient Transformers

Reference 2024

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Observation d9d954d7-5fd8-4243-8ac5-8a64c81343ed · outbound

This paper cites This protocol differs from LoRA-Ensemble’s own configuration in its optimisation scheme and ensemble size (M= 4here, versusM= 16in their paper).

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation This protocol differs from LoRA-Ensemble’s own configuration in its optimisation scheme and ensemble size (M= 4here, versusM= 16in their paper)

Reference 2025

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Observation 25aa26dd-0e7e-4294-bf0f-77a16f5f556b · outbound

This paper cites Dan Hendrycks and Thomas Dietterich.

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation Dan Hendrycks and Thomas Dietterich

Reference 2026

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Pith citing papers

No inbound Pith citation observations are available.