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Paper Citation Record · LEDGER

Adapting Auxiliary Losses Using Gradient Similarity

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:1812.02224.

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

pith.paper-citation-record.v1
1812.02224 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:09:53.907440Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

95
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 76b2cee8-cc0e-463e-9b1f-ffa00e610efd · inbound

Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss cites this paper.

Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss Adapting Auxiliary Losses Using Gradient Similarity

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:45:58.545952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-24T03:44:45.843249Z digest=sha256:cc1f8d2a8907e19861b659ddd8beed034f68eec9f9d1a5697b4182094a53aff0

Observation 4b3be87f-bb72-460c-a6e4-7105fdf137d7 · inbound

Effective Reward Specification in Deep Reinforcement Learning cites this paper.

Effective Reward Specification in Deep Reinforcement Learning Adapting Auxiliary Losses Using Gradient Similarity

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-11T19:09:53.907440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:09:53.907440Z digest=sha256:1e59f8c66eb1b23e4de49ff4037985a2f3474b435444045a552f63477446c177

Observation 1ecd527d-0ffa-4a93-88bd-5036c747f747 · inbound

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective cites this paper.

Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective Adapting Auxiliary Losses Using Gradient Similarity

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T00:18:15.854528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:18:15.854528Z digest=sha256:3085091c93f743859f869c38e5e717b0fd337b2b4d9afa8f03a28899661c658c

Observation 52d1e052-1648-407e-a701-f30c4224a965 · inbound

A Survey of State Representation Learning for Deep Reinforcement Learning cites this paper.

A Survey of State Representation Learning for Deep Reinforcement Learning Adapting Auxiliary Losses Using Gradient Similarity

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T23:34:34.373838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:34:34.373838Z digest=sha256:591491824eb995cccfea0d9e0d860a0aea3ff3db144409dd88367cde052aa9af

Observation a38369b5-c204-4799-b2bc-343d11fd34a1 · inbound

Understanding Knowledge Transferability for Transfer Learning: A Survey cites this paper.

Understanding Knowledge Transferability for Transfer Learning: A Survey Adapting Auxiliary Losses Using Gradient Similarity

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T20:22:24.333492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:24.333492Z digest=sha256:2b11cce12d2af4efb39f716634004bdd36c177aed9b1389d62bd3a19f21e4f09

Observation 2f23cd41-20b3-48c6-9f52-3558f0d4e668 · inbound

Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control cites this paper.

Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control Adapting Auxiliary Losses Using Gradient Similarity

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T12:16:02.213551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:16:02.213551Z digest=sha256:4fdb3402769877cf0c2b57e996f469222efce4a21a488d75d73da9982404b703

Observation 58e705e8-8057-4bf4-9957-7c9dcc7d57a5 · inbound

Unifying Search and Recommendation in LLMs via Gradient Multi-Subspace Tuning cites this paper.

Unifying Search and Recommendation in LLMs via Gradient Multi-Subspace Tuning Adapting Auxiliary Losses Using Gradient Similarity

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T10:41:38.684880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:41:38.684880Z digest=sha256:bd12c4772c8ec29e054edc108941998d7911b183521936bf2ec7ceb709fa9032

Observation 79c6b7ad-f3a8-4f75-bb99-e8a529818bc7 · inbound

Lorentz Framework for Semantic Segmentation cites this paper.

Lorentz Framework for Semantic Segmentation Adapting Auxiliary Losses Using Gradient Similarity

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:11:53.188474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T07:09:58.168604Z digest=sha256:202999b3b3c71534f80219d6e996a8b2138947b550b311da47873e41e00842cb

Observation 70316813-0b1e-4947-ac4e-0fdb89d36d78 · inbound

When Losses Align: Gradient-Based Composite Loss Weighting for Efficient Pretraining cites this paper.

When Losses Align: Gradient-Based Composite Loss Weighting for Efficient Pretraining Adapting Auxiliary Losses Using Gradient Similarity

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:15:54.976625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-11T03:11:37.361024Z digest=sha256:400ed1741581c7427801ed6ebffeff4ab764d8910c9e43376184719339003e12

Observation a8bacf80-908c-47b5-a077-63ca47e32fff · inbound

Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations cites this paper.

Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations Adapting Auxiliary Losses Using Gradient Similarity

Reference 133

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T06:29:41.800871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-21T06:29:04.835827Z digest=sha256:624aa20acf1b57bbc10a7067c494c7962366c7ce4e5231442466836793e93af8

Observation f9a6ac86-6df1-4112-9bc4-6de424a17683 · inbound

Mitigating Gradient Pathology in PINNs through Aligned Constraint cites this paper.

Mitigating Gradient Pathology in PINNs through Aligned Constraint Adapting Auxiliary Losses Using Gradient Similarity

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T12:44:39.342787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-30T12:39:26.604336Z digest=sha256:0b8a553dd55676a1d5945efd84bbfb4004264c4565c3f8ef4602d2724e8ace3a

Observation 56e6f109-a127-4da5-9ef3-235f6f85291b · inbound

T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation cites this paper.

T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation Adapting Auxiliary Losses Using Gradient Similarity

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:34:21.938395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-30T07:26:05.735508Z digest=sha256:6063704e441858479801729106f00a3196ada9c4a982d53c721a1ef0f339840b

Observation adced5e6-0222-47ea-89d0-6cd9c6ccc099 · inbound

Lantern: Conflict-Aware Gradient Blending for Physics-Guided Diffusion Models in Calorimeter Simulation cites this paper.

Lantern: Conflict-Aware Gradient Blending for Physics-Guided Diffusion Models in Calorimeter Simulation Adapting Auxiliary Losses Using Gradient Similarity

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-31T02:22:20.429673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:22:20.429673Z digest=sha256:19e9811401b7576079d0a0bbcfe396a43cb752028b6b4757ca340915b3893f9e