Paper Citation Record · LEDGER

Interpretable Emergent Language Using Inter-Agent Transformers

As of 20 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2505.02215.

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

pith.paper-citation-record.v1
2505.02215 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:01:46.074569Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:11:33.962656Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:11:35.247546Z

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy2
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c369dae9-241b-4da5-a0e1-3df990c9b094 · outbound

This paper cites TarMAC: Targeted Multi-Agent Communication.

Interpretable Emergent Language Using Inter-Agent Transformers TarMAC: Targeted Multi-Agent Communication

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:45.975984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 164ed6ed-2497-4fa1-82fb-d3e2a6c59b22 · outbound

This paper cites Learning to Communicate with Deep Multi-Agent Reinforcement Learning.

Interpretable Emergent Language Using Inter-Agent Transformers Learning to Communicate with Deep Multi-Agent Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:45.983547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68926db1-ff9c-4a07-8fe2-637460b4db1d · outbound

This paper cites Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols.

Interpretable Emergent Language Using Inter-Agent Transformers Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:45.990435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d374c8c-aa70-433a-85a2-b31f3c610a08 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Interpretable Emergent Language Using Inter-Agent Transformers Categorical Reparameterization with Gumbel-Softmax

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:45.997186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 011dc12b-6673-40e3-bb14-451332afbd28 · outbound

This paper cites Learning Attentional Communication for Multi-Agent Cooperation.

Interpretable Emergent Language Using Inter-Agent Transformers Learning Attentional Communication for Multi-Agent Cooperation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.008676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7037d151-61ea-4c3c-b840-7c97b6bbce80 · outbound

This paper cites Communication in multi-agent reinforcement learning: Intention sharing.

Interpretable Emergent Language Using Inter-Agent Transformers Communication in multi-agent reinforcement learning: Intention sharing

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:01:46.383021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ad84a8ee-180b-4220-a08b-b711091b60c0 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Interpretable Emergent Language Using Inter-Agent Transformers Adam: A Method for Stochastic Optimization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.023603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd0b7d2b-89c5-4206-bbed-69658483defc · outbound

This paper cites Convention: A philosophical study.

Interpretable Emergent Language Using Inter-Agent Transformers Convention: A philosophical study

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.030100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc4fd33d-aa2c-4140-81c8-d98bab10d1f8 · outbound

This paper cites Emergence of Grounded Compositional Language in Multi-Agent Populations.

Interpretable Emergent Language Using Inter-Agent Transformers Emergence of Grounded Compositional Language in Multi-Agent Populations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.035582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fce53b7a-a1ab-4337-94e3-196fecbc8614 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Interpretable Emergent Language Using Inter-Agent Transformers Proximal Policy Optimization Algorithms

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.041427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bd319fd-160c-4cbd-8682-549a90ba8f74 · outbound

This paper cites Learning Multiagent Communication with Backpropagation.

Interpretable Emergent Language Using Inter-Agent Transformers Learning Multiagent Communication with Backpropagation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.046708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 691468ad-e29b-4c62-8dd5-12178a40651f · outbound

This paper cites Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures.

Interpretable Emergent Language Using Inter-Agent Transformers Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.052994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 519f5ecf-f1b8-423b-afcc-bd187a4e1d36 · outbound

This paper cites Visualizing data using t-sne.

Interpretable Emergent Language Using Inter-Agent Transformers Visualizing data using t-sne

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.060164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2422633b-3ebe-4f51-9346-ae478c3fc1a3 · outbound

This paper cites Gomez, ukasz Kaiser, and Illia Polosukhin.

Interpretable Emergent Language Using Inter-Agent Transformers Gomez, ukasz Kaiser, and Illia Polosukhin

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T01:01:46.066396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 893faf25-ca78-4635-bb5c-62bec54f007e · outbound

This paper cites A survey of multi-agent deep reinforcement learning with communication.

Interpretable Emergent Language Using Inter-Agent Transformers A survey of multi-agent deep reinforcement learning with communication

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:01:46.339329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 5ec078f5-071d-44bf-984e-ff76d6f02985 · inbound

Wanting to Be Understood Explains the Meta-Problem of Consciousness cites this paper.

Wanting to Be Understood Explains the Meta-Problem of Consciousness Interpretable Emergent Language Using Inter-Agent Transformers

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:11:35.250348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.