Paper Citation Record · LEDGER

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2501.10945.

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

pith.paper-citation-record.v1
2501.10945 v3

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 2026-08-07T06:34:17.273281+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:35:18.515698Z

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

1
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 2375f3da-7836-4cf5-acb5-f899629d6857 · inbound

SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation cites this paper.

SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:35:18.515698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f853c627-d638-445d-8cf9-07bf71d0a470 · inbound

Identifying Offline Metrics that Predict Online Impact: A Pragmatic Strategy for Real-World Recommender Systems cites this paper.

Identifying Offline Metrics that Predict Online Impact: A Pragmatic Strategy for Real-World Recommender Systems Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:56:01.887726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ec6d288-1920-465e-8e6e-307d19efda0c · inbound

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

Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T12:16:02.188634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ae9456a-0b9b-4c0b-b950-ebaa72fc891b · inbound

Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs cites this paper.

Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:01:21.183657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a181ac67-39c4-4865-b572-2cff76decca1 · inbound

ML-Assisted Bulk Resource Allocation: Custom Outage-Based Loss Function and Reliability Analysis cites this paper.

ML-Assisted Bulk Resource Allocation: Custom Outage-Based Loss Function and Reliability Analysis Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T19:54:57.315865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e30a1e36-6093-49e8-a6e5-f85716f9e222 · inbound

Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting cites this paper.

Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T05:41:02.415494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93770fed-89f5-4d04-9279-89333b33092c · inbound

MGDA-Decoupled: Geometry-Aware Multi-Objective Optimisation for DPO-based LLM Alignment cites this paper.

MGDA-Decoupled: Geometry-Aware Multi-Objective Optimisation for DPO-based LLM Alignment Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-10T01:40:55.338358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc8747a3-7e90-4ed8-be08-7edee404cda5 · inbound

Distributionally Robust Multi-Objective Optimization cites this paper.

Distributionally Robust Multi-Objective Optimization Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 68

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:36:08.416993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 64a73575-e34c-45e3-a2e4-e0bdf97e6184 · inbound

Common-agency Games for Multi-Objective Test-Time Alignment cites this paper.

Common-agency Games for Multi-Objective Test-Time Alignment Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 191

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:15:06.678715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3da75aa8-0cf0-49b4-8905-f0eb1490580e · inbound

SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front cites this paper.

SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:44:00.918595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4145171f-bac6-4090-9254-ce69f3fb5522 · inbound

MAdam: Metric-Aware Multi-Objective Adam cites this paper.

MAdam: Metric-Aware Multi-Objective Adam Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:56:28.449364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 24845e79-6056-462a-a545-3a8fb0deca28 · inbound

Multi-Objective Exploration and Preference Optimization via Mutual Information cites this paper.

Multi-Objective Exploration and Preference Optimization via Mutual Information Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 65

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T21:18:57.955389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 561d1f28-4321-49cc-ab5b-162f56597890 · inbound

Improved Convergence Rate for Stochastic Multi-Gradient Descent: A Proof Discovered with AI cites this paper.

Improved Convergence Rate for Stochastic Multi-Gradient Descent: A Proof Discovered with AI Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T15:58:23.446589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.