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Paper Citation Record · LEDGER

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.22781.

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

pith.paper-citation-record.v1
2607.22781 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:39:35.951893Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

30 of 30 outbound references displayed

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External citation measurements

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Outbound references

Observation 66ce7296-48d5-4907-b5d9-fcfd4553a097 · outbound

This paper cites Towards better evaluation for dynamic link prediction,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Towards better evaluation for dynamic link prediction,

Reference 1

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Observation 8e80074f-d751-4182-903b-f66c91e7ae39 · outbound

This paper cites On the power of heuristics in temporal graphs,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation On the power of heuristics in temporal graphs,

Reference 2

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Observation 3a0fad89-0582-4806-88ab-9fc9d9bb689e · outbound

This paper cites What Do Temporal Graph Learning Models Learn?.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation What Do Temporal Graph Learning Models Learn?

Reference 3

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Observation 13c49549-6612-431d-8aae-0495e29a1e0c · outbound

This paper cites Attention is all you need,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Attention is all you need,

Reference 4

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Observation ab6c9d43-5310-4451-b516-7c5aa949f8e7 · outbound

This paper cites Inductive representation learning on temporal graphs,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Inductive representation learning on temporal graphs,

Reference 5

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Observation e175949c-a8dc-48ca-aa70-8379523152b5 · outbound

This paper cites Do we really need complicated model architectures for temporal networks?.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Do we really need complicated model architectures for temporal networks?

Reference 6

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Observation 47b34c7c-eea1-423e-86d7-67b0c1adda22 · outbound

This paper cites Towards better dynamic graph learning: New architecture and unified library,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Towards better dynamic graph learning: New architecture and unified library,

Reference 7

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Observation c72fc159-4473-4c7f-b25f-98de02588dac · outbound

This paper cites Future link prediction without memory or aggregation,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Future link prediction without memory or aggregation,

Reference 8

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Observation 21b86f7e-e0f7-4d46-acdd-e86d2bf68555 · outbound

This paper cites Understanding intermediate layers using linear classifier probes,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Understanding intermediate layers using linear classifier probes,

Reference 9

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Observation 66f88b78-3841-40b2-8794-87acbfc9121e · outbound

This paper cites What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties,

Reference 10

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Observation c45d3e01-2531-4459-ad54-76ab4f64fecf · outbound

This paper cites Designing and interpreting probes with control tasks,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Designing and interpreting probes with control tasks,

Reference 11

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Observation 7bd7ee1f-7a42-4c6a-b852-acdf0b990dfa · outbound

This paper cites Classifier probes may just learn from linear context features,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Classifier probes may just learn from linear context features,

Reference 12

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Observation e168b132-b4e2-4668-95c2-ec243bc7e9ba · outbound

This paper cites Improving attention mechanism in graph neural networks via cardinality preservation,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Improving attention mechanism in graph neural networks via cardinality preservation,

Reference 13

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Observation 8eb7ee61-7303-439d-80e1-a089b80a1a5a · outbound

This paper cites Normalized Attention Without Probability Cage.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Normalized Attention Without Probability Cage

Reference 14

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Observation 28f99b3d-fec4-40ae-bd6a-05332f0a9df0 · outbound

This paper cites Affine-scaled attention: Towards flexible and stable transformer attention,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Affine-scaled attention: Towards flexible and stable transformer attention,

Reference 15

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Observation 9200dc49-65ad-4894-a594-ab2d6a70df54 · outbound

This paper cites Recurrent marked temporal point processes: Embedding event history to vector,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Recurrent marked temporal point processes: Embedding event history to vector,

Reference 16

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Observation 1b06fcfd-e017-4227-b045-6e8ee2a15614 · outbound

This paper cites The neural hawkes process: A neurally self-modulating multivariate point process,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation The neural hawkes process: A neurally self-modulating multivariate point process,

Reference 17

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Observation ed51425e-868a-48bb-b3b8-caeaea9b3232 · outbound

This paper cites Transformer hawkes process,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Transformer hawkes process,

Reference 18

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Observation 01195efa-551c-4ea1-9664-b0742d8fa90b · outbound

This paper cites Transformer embeddings of irregularly spaced events and their participants,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Transformer embeddings of irregularly spaced events and their participants,

Reference 19

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Observation 0fd3b95b-d7b4-40d7-b5ec-40d01ba0121f · outbound

This paper cites Recurrent event network: Au- toregressive structure inference over temporal knowledge graphs,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Recurrent event network: Au- toregressive structure inference over temporal knowledge graphs,

Reference 20

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Observation ed3b383c-f6dc-4e28-a810-1c939d94b6d3 · outbound

This paper cites Explainable subgraph reasoning for forecasting on temporal knowledge graphs,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Explainable subgraph reasoning for forecasting on temporal knowledge graphs,

Reference 21

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Observation 804164d1-ffb0-4ff1-ae71-192ea488ae53 · outbound

This paper cites Learning from history: Modeling temporal knowledge graphs with sequential copy-generation networks,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Learning from history: Modeling temporal knowledge graphs with sequential copy-generation networks,

Reference 22

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Observation 81002c6c-96a9-4357-bbba-81f98a245bc2 · outbound

This paper cites HotpotQA: A dataset for diverse, explainable multi-hop question answering,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation HotpotQA: A dataset for diverse, explainable multi-hop question answering,

Reference 23

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Observation 1c94e930-95ac-42ce-960a-b318836c0651 · outbound

This paper cites Leveraging passage retrieval with generative models for open domain question answering,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Leveraging passage retrieval with generative models for open domain question answering,

Reference 24

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Observation 852c2187-1cd6-446b-b778-915738720ee2 · outbound

This paper cites Neural spatio-temporal point processes,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Neural spatio-temporal point processes,

Reference 25

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Observation 28416329-bbd6-4ca6-a794-b54e7690f821 · outbound

This paper cites Neural point process for learning spatiotemporal event dynamics,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Neural point process for learning spatiotemporal event dynamics,

Reference 26

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Observation 8d92e767-3cff-4888-a397-5350d588534b · outbound

This paper cites Layer Normalization.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Layer Normalization

Reference 27

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Observation 1ef1cb86-ce00-4154-8d9d-b5a09869fba9 · outbound

This paper cites On layer normalization in the transformer architecture,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation On layer normalization in the transformer architecture,

Reference 28

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Observation 3eb3b75c-c788-4900-b1c1-c44bbb118ebd · outbound

This paper cites Predicting dynamic embed- ding trajectory in temporal interaction networks,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Predicting dynamic embed- ding trajectory in temporal interaction networks,

Reference 29

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Observation 6193663a-f897-475d-aa67-33444527a7a4 · outbound

This paper cites Emergence of scaling in random networks,.

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation Emergence of scaling in random networks,

Reference 30

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