Pith. sign in

Paper Citation Record · LEDGER

Counterfactual Multi-Agent Policy Gradients

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1705.08926.

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

pith.paper-citation-record.v1
1705.08926 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:50:49.791457Z

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

478
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 c21374de-a97b-4c88-8cab-d545eb51d4c4 · inbound

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints cites this paper.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Counterfactual Multi-Agent Policy Gradients

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-24T23:15:03.085814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T23:14:06.926188Z digest=sha256:f1676ee3466630553c3b03dfcb9710d6e45e3fdd20b3d5c12e6a9144614d083a

Observation 25afa118-a762-45d8-bcf8-a40261e06d0a · inbound

Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning cites this paper.

Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning Counterfactual Multi-Agent Policy Gradients

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T18:50:49.791457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:50:49.791457Z digest=sha256:d59ab70d01b2dd99687dba8b29f6450cfd5583b3387cb3375eaaede2a0eda915

Observation 433f8291-d7e6-42ed-b59a-90a9e52d0579 · inbound

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications cites this paper.

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications Counterfactual Multi-Agent Policy Gradients

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:10:42.409639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:10:42.409639Z digest=sha256:5c5b8ff1fb371a9bbb803f51fe7423114a6aca0b7a5fe34af252adbf51096670

Observation 4e249290-a987-4389-8896-72faefb8fcfd · inbound

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration cites this paper.

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration Counterfactual Multi-Agent Policy Gradients

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T17:49:13.021222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:49:13.021222Z digest=sha256:151986ccb4ab8955eac0a79ec6904257654dcd027f783615e6d35f0f41c31ee0

Observation 0890aa05-1d1b-4669-bf9c-3717d62ea6a2 · inbound

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks cites this paper.

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks Counterfactual Multi-Agent Policy Gradients

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:55:58.977402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:55:19.978358Z digest=sha256:097132f1507fecf4823f1ff8d87580a41dfc9f94f9f59c15675a20120f0f5a0f

Observation 1051b446-624c-4808-af50-d85e1d6274a7 · inbound

Scalable Neighborhood-Based Multi-Agent Actor-Critic cites this paper.

Scalable Neighborhood-Based Multi-Agent Actor-Critic Counterfactual Multi-Agent Policy Gradients

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T09:23:38.028231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T05:19:42.391924Z digest=sha256:d11263f4cc9c5468c35dd4589d241b6ea37c79e246df11bcf600e2b89cc2d7b4

Observation fc595642-b1f5-4e6d-bec1-1bd691d7702c · inbound

Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning cites this paper.

Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning Counterfactual Multi-Agent Policy Gradients

Reference 133

Resolution
verified exact
arxiv_id, observed 2026-06-30T22:15:05.861082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-30T22:11:35.277901Z digest=sha256:6b2705212ec8457b6d11b9472b53dd699d83da399f793464d549b0639e573619

Observation 29654992-7f5c-4936-9eea-b3c316af76ea · inbound

DecompRL: Solving Harder Problems by Learning Modular Code Generation cites this paper.

DecompRL: Solving Harder Problems by Learning Modular Code Generation Counterfactual Multi-Agent Policy Gradients

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:38:39.731426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-03T16:30:34.793328Z digest=sha256:4dcf578d9ccf99e1989479d0d17cd50b66f4e3175b314be78016d3859b9d8844

Observation 46eb2973-743d-420d-97b5-84732b839668 · inbound

Training Large Language Models for Self-Explanation Faithfulness cites this paper.

Training Large Language Models for Self-Explanation Faithfulness Counterfactual Multi-Agent Policy Gradients

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-01T08:36:27.185275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T08:36:27.185275Z digest=sha256:97831732c455f2a21a0e7b96013666fca58a7fd3e17b47ec2b71d5557bee6808

Observation 48f5b4bb-33f2-428a-b4f6-eb41387ddcd7 · inbound

MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation cites this paper.

MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation Counterfactual Multi-Agent Policy Gradients

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-31T21:55:17.253357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T21:55:17.253357Z digest=sha256:e42dce49e85e1a7843e67556aea4e354c1d9e9bdbeaa4e8e9c8822826ad94fa4