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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=sha256:1359159058998bbd4b7e0cd43493e58d3915b58265812a39140392d8727ef473

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=sha256:1e37f07b0c098587286c134471f45225576097ce6473a9eb70be9a8465da9ec4

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

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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=sha256:6182f8ee35277981e49ac26497fa2c6a96483c5c570fe98efb52cf11e21870a5

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:b27b3bb33a8bbba39d426fad080f54ee842c0d4c77785c7e17f106c0e6cbfb85

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=sha256:0e40efc6c41bbfdb6715a3741adbbc1bb8221abd2ca0e3fe1ae531f2be96a71e

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=sha256:804008e99c036f7194cb5acf11a786fba285061f7bd6197e552ba1e6cd24d08d

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:ba895a290a53c9b0b7732d83f3c52fd07a664d0abbd3190d8f24f517501f5586

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=sha256:3877decbb30c608c2278e64060897f81dfaf1f39598e3c19482610f27bacddaa

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:bb7f718ce8a518cdcfe074265a38a7443b0a1bd741f46157b1211bc48f85e1a5

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=sha256:2372a57664a86b000394b3e54591968f5dc1616675184125648c7c8a5062fa83

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:d4193a74fb51e6842f9a57dd5d8a0c6567459f1a41fbbbc2c79072ebe7344445

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=sha256:6faff9e4fd180185da4e7c3dd765ac611f484d758a50cac663ef67c6ecbb5d53

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=sha256:6134bf4593c31654438f217271d4ebc0d24c894284c02d5ffca7ac6eacd675db

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:fd1101e1974f71fff37bc0409da5fa6e24e5c421647cc5bf5fa44ffa2ad10498

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:b9fa08ad20ea77c016c7c7390d1a534788d7a788aea7a74f8da74a0beba252e9

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:d61a844c58b4c4313a350beec3acdfa7b1be2d170ff5127f7e8f4e3db6018eeb

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=sha256:842afd95bcd3f556e2e280bfcf35d8947efbdadeae88d2b7ae215d52df1e4b64

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=sha256:3a8b422a9ddc02722fc2868d7c2bda602bc80a1ad885d0434a140b14e97680b0

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=sha256:3f98af71d4a833c4de4ff91fe6472a7612372ce7f44c0ddec96d6db8bf657dec

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:d6853aa0460d6f872cc812bfcd1e29a9f70f5ccbce90c5815e5b91098a68806e

Pith citing papers

No inbound Pith citation observations are available.