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Paper Citation Record · LEDGER

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension

As of 16 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:1908.05117.

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

pith.paper-citation-record.v1
1908.05117 v3

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:25:16.301672Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ae6cdec-0115-4631-9524-1c74d1202b48 · outbound

This paper cites URL: " 'urlintro :=.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension URL: " 'urlintro :=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.203369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.203369Z digest=sha256:6a858b232c6885f3ede744eb9e833b9144649bfff2f753c44d339fbaee027f4d

Observation 3be1b737-b0e3-4be6-9e88-11b9d98bff02 · outbound

This paper cites write newline.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension write newline

Reference 2

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unresolved
no resolver link, observed 2026-08-14T13:25:16.208932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.208932Z digest=sha256:2b99b8a2e43bc0ae400ef6a865c7f047bcc2663991df4f2d7fd379c71a970290

Observation 19b1b8e4-c29f-4419-9b61-56f059133761 · outbound

This paper cites Layer Normalization.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Layer Normalization

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.213863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.213863Z digest=sha256:1786fee754537c451d620fb3053be9eb353420bcd9b1a4edeb6ee54703778322

Observation 98093aa8-307c-4ec3-9333-077e1634b5e9 · outbound

This paper cites an unresolved cited work.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:25:16.617327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T13:25:16.219439Z digest=sha256:82e0e12022c36dce2859437d89b21296d724c3631ee05064556f0d2e886ca07d

Observation 7971358c-2501-4f56-b72f-b1ff8cff15aa · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.224082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.224082Z digest=sha256:2508ff83e859e0a2971b888d82c984fa0d7c73239bd181a1bb8dafd711108acb

Observation 2cd8737d-3468-4725-aaac-375f9e6e1e35 · outbound

This paper cites Unified Pragmatic Models for Generating and Following Instructions.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Unified Pragmatic Models for Generating and Following Instructions

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.228977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.228977Z digest=sha256:fe3bdc3336d2000476030355d5a8bb815e88261f60e81e4f6c849d03aac44e98

Observation 7730a968-a6ef-4adb-894f-6e084ccd0011 · outbound

This paper cites From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.234829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.234829Z digest=sha256:de0b63748df13e021d89d430c00fe9bb79cb590987744ea6db52f3a82053addb

Observation f76ae298-ce02-46d4-b93f-96522897bee2 · outbound

This paper cites FlowQA: Grasping Flow in History for Conversational Machine Comprehension.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension FlowQA: Grasping Flow in History for Conversational Machine Comprehension

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.239631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.239631Z digest=sha256:d1af33f042a60db7163403238022839481b7295a2f1d47403e31d4c357de4c24

Observation ea233c72-cfd6-40b6-8ccf-1a2a54d7c7cf · outbound

This paper cites FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.245221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.245221Z digest=sha256:d2c18b3fc59de426e79eab77020664e08d74e0a82239f970ac2dd0ad0c24653c

Observation dfb391e7-c4e4-4a67-a933-ace132cb744e · outbound

This paper cites Simpler Context-Dependent Logical Forms via Model Projections.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Simpler Context-Dependent Logical Forms via Model Projections

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.250110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.250110Z digest=sha256:1d357b8ab301b39bbde64992ff388c073b786f59bf639a1a9b19ecd52ab9a66e

Observation 6755337d-35f7-4080-bfbb-6ed228225577 · outbound

This paper cites an unresolved cited work.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:25:16.602737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T13:25:16.255753Z digest=sha256:a4a98461339a6c26b7d35a662799db9720694ee334db238e21167484284de493

Observation e0add528-a5f2-4997-a6b4-566a41e18e5f · outbound

This paper cites Know What You Don't Know: Unanswerable Questions for SQuAD.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Know What You Don't Know: Unanswerable Questions for SQuAD

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.260737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.260737Z digest=sha256:e2381048acc26b4c633a7b411a795815bb800ff207d32b20d37e9d22e5de0c2f

Observation 4a2f28ef-a597-40e6-9b1b-b3044b071388 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.265736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.265736Z digest=sha256:bb2afb073ca57579f9e521eff62aed44bf9acb02c38030a83e0721ef212ef7a1

Observation 9cafd0d6-ea0d-4110-950d-5a316ebf3ae3 · outbound

This paper cites CoQA: A Conversational Question Answering Challenge.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension CoQA: A Conversational Question Answering Challenge

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.270801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.270801Z digest=sha256:922f0fc7c575990a0da3a027976251789b4480ded0d8612d7713220a05e6d2dc

Observation d93a1405-b8c4-433f-b4ba-3d511147d8ec · outbound

This paper cites BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.275618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.275618Z digest=sha256:21e9b96bbcdc2e833a334448ff2fa173e1af2fc720da44e6683be85e238d9d72

Observation 0a1d3873-a497-4ded-820e-251f612411ad · outbound

This paper cites Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observation.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observation

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:25:16.400185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T13:25:16.280455Z digest=sha256:4dd98067a924ce62f865a833ca0af7f628b4b820748e91152ab56c03e73dff46

Observation 27401151-1ed5-474a-82f7-f418fe377cb4 · outbound

This paper cites an unresolved cited work.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.285730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.285730Z digest=sha256:1290725153737911691e7e0d68509b0d50ff3fad684f15b0e8e7c500bb67d7a9

Observation 21d4febd-58cc-4a24-a903-cf8e7129112a · outbound

This paper cites A Qualitative Comparison of CoQA, SQuAD 2.0 and QuAC.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension A Qualitative Comparison of CoQA, SQuAD 2.0 and QuAC

Reference 18

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unresolved
no resolver link, observed 2026-08-14T13:25:16.290332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.290332Z digest=sha256:584dcfcddce77ee1307d84a163ef9c1af7bc4f6939f84ccc0639a1aa2114364d

Observation f614e82b-149b-4b64-acce-91d137c794c2 · outbound

This paper cites QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.295210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.295210Z digest=sha256:8f6a8366c2b7b4f3809d4e359cc474d5554c3dd1e621c6df5360ac8778367660

Observation 96349b1b-e962-4ec2-accf-bdde8722f1b1 · outbound

This paper cites SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-14T13:25:16.301672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:25:16.301672Z digest=sha256:f55f3068fda8efbdced2a550840b559a6fbcb520499910721e65b8fdc16bcc69

Pith citing papers

No inbound Pith citation observations are available.